Spatial Data Regression Modeling Action Set

Provides an action for modeling spatial data

spatialreg Action

Analyzes regression models for spatial data.

CASL Syntax

spatialreg.spatialreg <result=results> <status=rc> /

bounds={"string-1" <, "string-2", ...>},

class={{

countMissing=TRUE | FALSE,

descending=TRUE | FALSE,

ignoreMissing=TRUE | FALSE,

maxLev=integer,

order="FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL",

ref="FIRST" | "LAST" | double | "string",

vars={"variable-name-1" <, "variable-name-2", ...>}

}, {...}},

display={

caseSensitive=TRUE | FALSE,

exclude=TRUE | FALSE,

excludeAll=TRUE | FALSE,

keyIsPath=TRUE | FALSE,

names={"string-1" <, "string-2", ...>},

pathType="LABEL" | "NAME",

traceNames=TRUE | FALSE

impact={

nmc=integer,

order=integer,

seed=integer

includeinternalnames=TRUE | FALSE,

initialvalues={"string-1" <, "string-2", ...>},

model={

depVars={{

name="variable-name"

}, {...}},

effects={{

interaction="BAR" | "CROSS" | "NONE",

maxInteract=integer,

nest={"string-1" <, "string-2", ...>},

vars={"string-1" <, "string-2", ...>}

}, {...}},

modeloptions={

corrb=TRUE | FALSE

covb=TRUE | FALSE

modelLabel="string"

modeltype="ALL" | "AUTO" | "CAR" | "LINEAR" | "SAC" | "SAR" | "SARMA" | "SEM" | "SMA"

noint=TRUE | FALSE

montecarloapprox={

method="CHEBYSHEV" | "TAYLOR",

nmc=integer,

order=integer,

seed=integer

nonormalizeWMatrix=TRUE | FALSE,

optimizer={

aftl=double,

agtl=double,

atol=double,

axtl=double,

ceps=double,

covestmethod="CROSSOP" | "HESSIAN" | "QML",

ftol=double,

gtol=double,

iterationHistory={

basic=TRUE | FALSE

estimatesForEachStep=TRUE | FALSE

olsEstimates=TRUE | FALSE

maxf=double,

maxit=double,

maxtime=double,

sing=double,

sweepSing=double

output={

casOut={

caslib="string"

compress=TRUE | FALSE

indexVars={"variable-name-1" <, "variable-name-2", ...>}

label="string"

lifetime=64-bit-integer

maxMemSize=64-bit-integer

memoryFormat="DVR" | "INHERIT" | "STANDARD"

name="table-name"

onDemand=TRUE | FALSE

promote=TRUE | FALSE

replace=TRUE | FALSE

replication=integer

threadBlockSize=64-bit-integer

timeStamp="string"

where={"string-1" <, "string-2", ...>}

copyVars="ALL" | "ALL_MODEL" | "ALL_NUMERIC" | {"variable-name-1" <, "variable-name-2", ...>},

pred="string",

resid="string",

xbeta="string"

outputTables={

groupByVarsRaw=TRUE | FALSE,

includeAll=TRUE | FALSE,

names={"string-1" <, "string-2", ...>} | {key-1={casouttable-1} <, key-2={casouttable-2}, ...>},

repeated=TRUE | FALSE,

replace=TRUE | FALSE

restrictions={"string-1" <, "string-2", ...>},

spatialeffects={

depVars={{

name="variable-name"

}, {...}},

effects={{

interaction="BAR" | "CROSS" | "NONE",

maxInteract=integer,

nest={"string-1" <, "string-2", ...>},

vars={"string-1" <, "string-2", ...>}

}, {...}}

spatialid="variable-name",

table={

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

groupBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

groupByMode="NOSORT" | "REDISTRIBUTE",

importOptions={fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DELIMITED" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SOUND" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters},

name="table-name",

onDemand=TRUE | FALSE,

orderBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=TRUE | FALSE,

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable={

casLib="string"

dataSourceOptions={adls_noreq-parameters | bigquery-parameters | cas_noreq-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | fedsvr-parameters | gcs_noreq-parameters | hadoop-parameters | hana-parameters | impala-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sforce-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

tests={{

eqns={"string-1" <, "string-2", ...>},

testLabel="string",

testNames={"string-1" <, "string-2", ...>}

}, {...}},

timingReport={

details=TRUE | FALSE,

summary=TRUE | FALSE

wmatrix={

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

groupBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

onDemand=TRUE | FALSE,

orderBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=TRUE | FALSE,

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable={

casLib="string"

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

;

indicates a required parameter

Summary: Input and Output Tables

If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
required parametertable	—	specifies the input data table.
wmatrix	—	specifies the input table of spatial weights.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
output	required parametercasOut	specifies details for an output data table to contain scores for various statistics.
outputTables	names	specifies the list of display tables that you want to output as CAS tables. If this parameter is not specified, no tables are output as CAS tables.

Parameter Descriptions

bounds={"string-1" <, "string-2", ...>}

imposes simple boundary constraints on the parameter estimates.

class={{classStatement-1} <, {classStatement-2}, ...>}

specifies the classification variables.

Alias	classVars

The classStatement value can be one or more of the following:

countMissing=TRUE | FALSE

when set to True, treats missing as a valid level for this variable.

Default	FALSE

descending=TRUE | FALSE

when set to True, reverses the sort order that is imposed by the order parameter.

Default	FALSE

ignoreMissing=TRUE | FALSE

when set to True, ignores the fact that some variables in the observation have missing values and honors the nonmissing values for other variables in that observation.

Default	FALSE

maxLev=integer

specifies the maximum number of levels. A value of 0 means an unlimited number of levels.

Default	0
Minimum value	0

order="FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL"

specifies the sort order for the levels of the classification variable. This ordering determines which parameters in the model correspond to each level in the data.

param="BTH" | "EFFECT" | "GLM" | "ORDINAL" | "ORTHBTH" | "ORTHEFFECT" | "ORTHORDINAL" | "ORTHPOLY" | "ORTHREF" | "POLYNOMIAL" | "REFERENCE"

specifies the parameterization method for the classification variable or variables. The default is GLM when none of the variables specified in the vars parameter includes a param parameter; otherwise, the default is REFERENCE.

ref="FIRST" | "LAST" | double | "string"

specifies the reference level to use when you specify a nonsingular parameterization in the param parameter. For an individual variable, you can specify the level of the variable to use as the reference level. If the action supports the global class options parameter, then you can specify FIRST or LAST.

* vars={"variable-name-1" <, "variable-name-2", ...>}

specifies the classification variables.

Alias	name

display={displayTables}

specifies the list of display tables that you want the action to create. If this parameter is not specified, all tables are created.

For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).

impact={ImpactEstOptions}

specifies impact estimation control options.

Alias	impactestimate

The ImpactEstOptions value can be one or more of the following:

nmc=integer

specifies the number of random draws for impact estimation.

Alias	ndraws
Minimum value	1

order=integer

specifies the order of Neumann series for impact estimation.

Alias	truncorder
Range	1–2000

seed=integer

specifies the seed for random number generation for impact estimation.

Alias	randomseed
Minimum value	1

includeinternalnames=TRUE | FALSE

when set to True, adds an extra column to the parameter estimates table that shows the internal names for the parameters.

Default	FALSE

initialvalues={"string-1" <, "string-2", ...>}

specifies initial values for parameters in the optimization.

* model={spregmodelstmt}

specifies the dependent variable and independent regressor variables for the regression model.

The spregmodelstmt value can be one or more of the following:

depVars={{responsevar-1} <, {responsevar-2}, ...>}

specifies one or more variables to use as response variables in the model. Not all models support more than one response variable.

Aliases	depVar
Aliases	target

name="variable-name"

names the response variable.

effects={{effect-1} <, {effect-2}, ...>}

specifies a list of effects that define the model. Each term in this list is made up of variables specified in the vars parameter and their interaction (which can be NONE, CROSS, or BAR). When the interaction is BAR, it can be limited by the maxInteract parameter.

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Alias	interact
Default	NONE

maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

nest={"string-1" <, "string-2", ...>}

specifies the variables to be nested within the term that is defined by the vars parameter. For terms with a BAR or CROSS interaction, the nest corresponds to the last variable in the vars parameter. For terms with no interaction, the nest is distributed across all variables that are listed in the vars parameter.

* vars={"string-1" <, "string-2", ...>}

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

modeloptions={modeloptions}

specifies options that you can apply to the model.

The modeloptions value can be one or more of the following:

corrb=TRUE | FALSE

when set to True, produces a table of the correlations of the parameter estimates.

Default	FALSE

covb=TRUE | FALSE

when set to True, produces a table of the covariances of the parameter estimates.

Default	FALSE

modelLabel="string"

specifies a label for the model.

modeltype="ALL" | "AUTO" | "CAR" | "LINEAR" | "SAC" | "SAR" | "SARMA" | "SEM" | "SMA"

specifies the type of model to be analyzed.

Default	SAR

ALL

analyzes all supported models

AUTO

analyzes selected multiple models

CAR

analyzes a conditional autoregressive model.

LINEAR

analyzes a linear model.

SAC

analyzes a spatial autoregressive confused model.

SAR

analyzes a spatial autoregressive model.

SARMA

analyzes a spatial autoregressive moving average model.

SEM

analyzes a spatial error model.

SMA

analyzes a spatial moving average model.

noint=TRUE | FALSE

when set to True, suppresses the intercept parameter.

Default	FALSE

noint=TRUE | FALSE

when set to True, does not include the intercept term in the model.

Default	FALSE

montecarloapprox={MCApproxOptions}

specifies Monte Carlo approximation control options.

Alias	approximation

Long form	montecarloapprox={method="CHEBYSHEV" \| "TAYLOR"}
Shortcut form	montecarloapprox="CHEBYSHEV" \| "TAYLOR"

The MCApproxOptions value can be one or more of the following:

method="CHEBYSHEV" | "TAYLOR"

specifies the type of approximation to use.

Alias	approxmethod
Default	CHEBYSHEV

nmc=integer

specifies the number of random draws for approximation.

Alias	ndraws
Minimum value	1

order=integer

specifies the order of series in the Taylor or Chebyshev approximation.

Alias	truncorder
Range	1–2000

seed=integer

specifies the seed for random number generation.

Alias	randomseed
Minimum value	1

nonormalizeWMatrix=TRUE | FALSE

when set to True, suppresses the row standardization of the spatial weights matrix.

Default	FALSE

optimizer={optimizerOpts}

specifies parameters that control various aspects of the parameter estimation process.

Long form	optimizer={algorithm="CONJUGATEGRADIENT" \| "DOUBLEDOGLEG" \| "NEWTONRAPHSONWITHLINESEARCH" \| "NEWTONRAPHSONWITHRIDGING" \| "NONE" \| "QUASINEWTON" \| "TRUSTREGION"}
Shortcut form	optimizer="CONJUGATEGRADIENT" \| "DOUBLEDOGLEG" \| "NEWTONRAPHSONWITHLINESEARCH" \| "NEWTONRAPHSONWITHRIDGING" \| "NONE" \| "QUASINEWTON" \| "TRUSTREGION"

The optimizerOpts value can be one or more of the following:

aftl=double

specifies an absolute function difference convergence criterion.

Aliases	absfconv
Aliases	absftol
Minimum value	0

agtl=double

specifies an absolute gradient convergence criterion.

Aliases	absgconv
Aliases	absgtol
Minimum value	0

algorithm="CONJUGATEGRADIENT" | "DOUBLEDOGLEG" | "NEWTONRAPHSONWITHLINESEARCH" | "NEWTONRAPHSONWITHRIDGING" | "NONE" | "QUASINEWTON" | "TRUSTREGION"

specifies the nonlinear optimization technique to use.

Aliases	technique
	tech
	method
Default	NEWTONRAPHSONWITHLINESEARCH

atol=double

specifies an absolute function convergence criterion.

axtl=double

specifies an absolute parameter convergence criterion.

Alias	absxconv
Minimum value	0

ceps=double

specifies the infeasibility tolerance applied to constraints (such as restrictions and bounds).

Aliases	lceps
Aliases	feastol
Minimum value	0

covestmethod="CROSSOP" | "HESSIAN" | "QML"

specifies the covariance estimation method to use.

Alias	covest
Default	HESSIAN

CROSSOP

specifies the covariance from the outer product matrix.

HESSIAN

specifies the covariance from the Hessian matrix.

QML

specifies the covariance from the outer product and Hessian matrix.

ftol=double

specifies a relative function difference convergence criterion.

Alias	fconv
Minimum value	0

gtol=double

specifies a relative gradient convergence criterion.

Alias	gconv
Minimum value	0

iterationHistory={iterationHistoryOpts}

when set to True, produces various tables that describe the iteration process.

The iterationHistoryOpts value can be one or more of the following:

basic=TRUE | FALSE

when set to True, produces a table that provides the basic optimization history.

Default	TRUE

estimatesForEachStep=TRUE | FALSE

when set to True, produces a table that provides the parameter estimates calculated at each iteration during the optimization process.

Default	FALSE

olsEstimates=TRUE | FALSE

when set to True, produces a table of the initial parameter estimates based on ordinary least squares estimation. The OLS estimate for a given parameter is ignored if you provide an initial value for that parameter.

Default	FALSE

maxf=double

specifies the maximum number of objective function evaluations in the optimization process.

Minimum value	0

maxit=double

specifies the maximum number of iterations in the optimization process.

Alias	maxiter
Minimum value	0

maxtime=double

specifies an upper limit (in seconds) on the CPU time for the optimization process.

Minimum value	0

sing=double

specifies the singularity criterion to use for the inversion of the Hessian matrix.

Minimum value	0

sweepSing=double

specifies the singularity criterion to use for the inversion of the SSCP matrix.

Minimum value	0

output={spregoutputStatement}

specifies details for an output data table to contain scores for various statistics.

The spregoutputStatement value can be one or more of the following:

* casOut={casouttable}

specifies the settings for an output table.

For more information about specifying the casOut parameter, see the common casouttable parameter (Appendix A: Common Parameters).

copyVars="ALL" | "ALL_MODEL" | "ALL_NUMERIC" | {"variable-name-1" <, "variable-name-2", ...>}

specifies a list of one or more variables to be copied from the input table to the output table. You can alternatively specify the value ALL, ALL_MODEL, or ALL_NUMERIC, which respectively copies all variables, all variables used in the modeling, or all numeric variables from the input table to the output table.

pred="string"

names the variable to contain the expected value of the response variable.

Aliases	expected
Aliases	mean

resid="string"

names the variable to contain the residual.

Alias	residual

xbeta="string"

names the variable to contain the estimates of xbeta.

Alias	xb

outputTables={outputTables}

specifies the list of display tables that you want to output as CAS tables. If this parameter is not specified, no tables are output as CAS tables.

For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).

Alias	displayOut

restrictions={"string-1" <, "string-2", ...>}

specifies linear restrictions to be imposed on the parameter estimates.

spatialeffects={slxmodelstmt}

specifies independent regressor variables whose spatial lag is to be added to the MODEL statement.

The slxmodelstmt value can be one or more of the following:

depVars={{responsevar-1} <, {responsevar-2}, ...>}

specifies one or more variables to use as response variables in the model. Not all models support more than one response variable.

Aliases	depVar
Aliases	target

name="variable-name"

names the response variable.

effects={{effect-1} <, {effect-2}, ...>}

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Alias	interact
Default	NONE

maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

nest={"string-1" <, "string-2", ...>}

* vars={"string-1" <, "string-2", ...>}

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

spatialid="variable-name"

specifies a variable that identifies an observation in two tables of input data and spatial weights.

Alias	sid

* table={castable}

specifies the input data table.

For more information about specifying the table parameter, see the common castable parameter (Appendix A: Common Parameters).

tests={{singleTest-1} <, {singleTest-2}, ...>}

specifies linear hypotheses about the regression parameters that are specified in the model and tests to be performed on the hypotheses (Wald, Lagrange multiplier, and likelihood ratio tests).

The singleTest value can be one or more of the following:

* eqns={"string-1" <, "string-2", ...>}

specifies a list of equations to be tested for a single test.

testLabel="string"

specifies a label to be assigned to a single test.

testNames={"string-1" <, "string-2", ...>}

specifies one or more of the tests (Wald, LM, and LR) to be applied to each equation in the list.

Default	WALD

timingReport={timingReportOpts}

specifies the type of timing information that you want the action to provide.

The timingReportOpts value can be one or more of the following:

details=TRUE | FALSE

when set to True, produces a detailed summary of the time used for all phases of execution.

Default	FALSE

summary=TRUE | FALSE

when set to True, produces a summary of the time used for the main phases of execution.

Default	FALSE

wmatrix={castable}

specifies the input table of spatial weights.

For more information about specifying the wmatrix parameter, see the common castable parameter (Appendix A: Common Parameters).

Alias	wmat

spatialreg Action

Analyzes regression models for spatial data.

Lua Syntax

results, info = s:spatialreg_spatialreg{

bounds={"string-1" <, "string-2", ...>},

class={{

countMissing=true | false,

descending=true | false,

ignoreMissing=true | false,

maxLev=integer,

order="FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL",

ref="FIRST" | "LAST" | double | "string",

vars={"variable-name-1" <, "variable-name-2", ...>}

}, {...}},

display={

caseSensitive=true | false,

exclude=true | false,

excludeAll=true | false,

keyIsPath=true | false,

names={"string-1" <, "string-2", ...>},

pathType="LABEL" | "NAME",

traceNames=true | false

impact={

nmc=integer,

order=integer,

seed=integer

includeinternalnames=true | false,

initialvalues={"string-1" <, "string-2", ...>},

model={

depVars={{

name="variable-name"

}, {...}},

effects={{

interaction="BAR" | "CROSS" | "NONE",

maxInteract=integer,

nest={"string-1" <, "string-2", ...>},

vars={"string-1" <, "string-2", ...>}

}, {...}},

modeloptions={

corrb=true | false

covb=true | false

modelLabel="string"

modeltype="ALL" | "AUTO" | "CAR" | "LINEAR" | "SAC" | "SAR" | "SARMA" | "SEM" | "SMA"

noint=true | false

montecarloapprox={

method="CHEBYSHEV" | "TAYLOR",

nmc=integer,

order=integer,

seed=integer

nonormalizeWMatrix=true | false,

optimizer={

aftl=double,

agtl=double,

atol=double,

axtl=double,

ceps=double,

covestmethod="CROSSOP" | "HESSIAN" | "QML",

ftol=double,

gtol=double,

iterationHistory={

basic=true | false

estimatesForEachStep=true | false

olsEstimates=true | false

maxf=double,

maxit=double,

maxtime=double,

sing=double,

sweepSing=double

output={

casOut={

caslib="string"

compress=true | false

indexVars={"variable-name-1" <, "variable-name-2", ...>}

label="string"

lifetime=64-bit-integer

maxMemSize=64-bit-integer

memoryFormat="DVR" | "INHERIT" | "STANDARD"

name="table-name"

onDemand=true | false

promote=true | false

replace=true | false

replication=integer

threadBlockSize=64-bit-integer

timeStamp="string"

where={"string-1" <, "string-2", ...>}

copyVars="ALL" | "ALL_MODEL" | "ALL_NUMERIC" | {"variable-name-1" <, "variable-name-2", ...>},

pred="string",

resid="string",

xbeta="string"

outputTables={

groupByVarsRaw=true | false,

includeAll=true | false,

names={"string-1" <, "string-2", ...>} | {key-1={casouttable-1} <, key-2={casouttable-2}, ...>},

repeated=true | false,

replace=true | false

restrictions={"string-1" <, "string-2", ...>},

spatialeffects={

depVars={{

name="variable-name"

}, {...}},

effects={{

interaction="BAR" | "CROSS" | "NONE",

maxInteract=integer,

nest={"string-1" <, "string-2", ...>},

vars={"string-1" <, "string-2", ...>}

}, {...}}

spatialid="variable-name",

table={

caslib="string",

computedOnDemand=true | false,

computedVars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

groupBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

onDemand=true | false,

orderBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=true | false,

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable={

casLib="string"

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

tests={{

eqns={"string-1" <, "string-2", ...>},

testLabel="string",

testNames={"string-1" <, "string-2", ...>}

}, {...}},

timingReport={

details=true | false,

summary=true | false

wmatrix={

caslib="string",

computedOnDemand=true | false,

computedVars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

groupBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

onDemand=true | false,

orderBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=true | false,

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable={

casLib="string"

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

indicates a required parameter

Summary: Input and Output Tables

If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
required parametertable	—	specifies the input data table.
wmatrix	—	specifies the input table of spatial weights.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
output	required parametercasOut	specifies details for an output data table to contain scores for various statistics.
outputTables	names	specifies the list of display tables that you want to output as CAS tables. If this parameter is not specified, no tables are output as CAS tables.

Parameter Descriptions

bounds={"string-1" <, "string-2", ...>}

imposes simple boundary constraints on the parameter estimates.

class={{classStatement-1} <, {classStatement-2}, ...>}

specifies the classification variables.

Alias	classVars

The classStatement value can be one or more of the following:

countMissing=true | false

when set to True, treats missing as a valid level for this variable.

Default	false

descending=true | false

when set to True, reverses the sort order that is imposed by the order parameter.

Default	false

ignoreMissing=true | false

when set to True, ignores the fact that some variables in the observation have missing values and honors the nonmissing values for other variables in that observation.

Default	false

maxLev=integer

specifies the maximum number of levels. A value of 0 means an unlimited number of levels.

Default	0
Minimum value	0

order="FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL"

specifies the sort order for the levels of the classification variable. This ordering determines which parameters in the model correspond to each level in the data.

param="BTH" | "EFFECT" | "GLM" | "ORDINAL" | "ORTHBTH" | "ORTHEFFECT" | "ORTHORDINAL" | "ORTHPOLY" | "ORTHREF" | "POLYNOMIAL" | "REFERENCE"

ref="FIRST" | "LAST" | double | "string"

* vars={"variable-name-1" <, "variable-name-2", ...>}

specifies the classification variables.

Alias	name

display={displayTables}

specifies the list of display tables that you want the action to create. If this parameter is not specified, all tables are created.

For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).

impact={ImpactEstOptions}

specifies impact estimation control options.

Alias	impactestimate

The ImpactEstOptions value can be one or more of the following:

nmc=integer

specifies the number of random draws for impact estimation.

Alias	ndraws
Minimum value	1

order=integer

specifies the order of Neumann series for impact estimation.

Alias	truncorder
Range	1–2000

seed=integer

specifies the seed for random number generation for impact estimation.

Alias	randomseed
Minimum value	1

includeinternalnames=true | false

when set to True, adds an extra column to the parameter estimates table that shows the internal names for the parameters.

Default	false

initialvalues={"string-1" <, "string-2", ...>}

specifies initial values for parameters in the optimization.

* model={spregmodelstmt}

specifies the dependent variable and independent regressor variables for the regression model.

The spregmodelstmt value can be one or more of the following:

depVars={{responsevar-1} <, {responsevar-2}, ...>}

specifies one or more variables to use as response variables in the model. Not all models support more than one response variable.

Aliases	depVar
Aliases	target

name="variable-name"

names the response variable.

effects={{effect-1} <, {effect-2}, ...>}

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Alias	interact
Default	NONE

maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

nest={"string-1" <, "string-2", ...>}

* vars={"string-1" <, "string-2", ...>}

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

modeloptions={modeloptions}

specifies options that you can apply to the model.

The modeloptions value can be one or more of the following:

corrb=true | false

when set to True, produces a table of the correlations of the parameter estimates.

Default	false

covb=true | false

when set to True, produces a table of the covariances of the parameter estimates.

Default	false

modelLabel="string"

specifies a label for the model.

modeltype="ALL" | "AUTO" | "CAR" | "LINEAR" | "SAC" | "SAR" | "SARMA" | "SEM" | "SMA"

specifies the type of model to be analyzed.

Default	SAR

ALL

analyzes all supported models

AUTO

analyzes selected multiple models

CAR

analyzes a conditional autoregressive model.

LINEAR

analyzes a linear model.

SAC

analyzes a spatial autoregressive confused model.

SAR

analyzes a spatial autoregressive model.

SARMA

analyzes a spatial autoregressive moving average model.

SEM

analyzes a spatial error model.

SMA

analyzes a spatial moving average model.

noint=true | false

when set to True, suppresses the intercept parameter.

Default	false

noint=true | false

when set to True, does not include the intercept term in the model.

Default	false

montecarloapprox={MCApproxOptions}

specifies Monte Carlo approximation control options.

Alias	approximation

Long form	montecarloapprox={method="CHEBYSHEV" \| "TAYLOR"}
Shortcut form	montecarloapprox="CHEBYSHEV" \| "TAYLOR"

The MCApproxOptions value can be one or more of the following:

method="CHEBYSHEV" | "TAYLOR"

specifies the type of approximation to use.

Alias	approxmethod
Default	CHEBYSHEV

nmc=integer

specifies the number of random draws for approximation.

Alias	ndraws
Minimum value	1

order=integer

specifies the order of series in the Taylor or Chebyshev approximation.

Alias	truncorder
Range	1–2000

seed=integer

specifies the seed for random number generation.

Alias	randomseed
Minimum value	1

nonormalizeWMatrix=true | false

when set to True, suppresses the row standardization of the spatial weights matrix.

Default	false

optimizer={optimizerOpts}

specifies parameters that control various aspects of the parameter estimation process.

Long form	optimizer={algorithm="CONJUGATEGRADIENT" \| "DOUBLEDOGLEG" \| "NEWTONRAPHSONWITHLINESEARCH" \| "NEWTONRAPHSONWITHRIDGING" \| "NONE" \| "QUASINEWTON" \| "TRUSTREGION"}
Shortcut form	optimizer="CONJUGATEGRADIENT" \| "DOUBLEDOGLEG" \| "NEWTONRAPHSONWITHLINESEARCH" \| "NEWTONRAPHSONWITHRIDGING" \| "NONE" \| "QUASINEWTON" \| "TRUSTREGION"

The optimizerOpts value can be one or more of the following:

aftl=double

specifies an absolute function difference convergence criterion.

Aliases	absfconv
Aliases	absftol
Minimum value	0

agtl=double

specifies an absolute gradient convergence criterion.

Aliases	absgconv
Aliases	absgtol
Minimum value	0

algorithm="CONJUGATEGRADIENT" | "DOUBLEDOGLEG" | "NEWTONRAPHSONWITHLINESEARCH" | "NEWTONRAPHSONWITHRIDGING" | "NONE" | "QUASINEWTON" | "TRUSTREGION"

specifies the nonlinear optimization technique to use.

Aliases	technique
	tech
	method
Default	NEWTONRAPHSONWITHLINESEARCH

atol=double

specifies an absolute function convergence criterion.

axtl=double

specifies an absolute parameter convergence criterion.

Alias	absxconv
Minimum value	0

ceps=double

specifies the infeasibility tolerance applied to constraints (such as restrictions and bounds).

Aliases	lceps
Aliases	feastol
Minimum value	0

covestmethod="CROSSOP" | "HESSIAN" | "QML"

specifies the covariance estimation method to use.

Alias	covest
Default	HESSIAN

CROSSOP

specifies the covariance from the outer product matrix.

HESSIAN

specifies the covariance from the Hessian matrix.

QML

specifies the covariance from the outer product and Hessian matrix.

ftol=double

specifies a relative function difference convergence criterion.

Alias	fconv
Minimum value	0

gtol=double

specifies a relative gradient convergence criterion.

Alias	gconv
Minimum value	0

iterationHistory={iterationHistoryOpts}

when set to True, produces various tables that describe the iteration process.

The iterationHistoryOpts value can be one or more of the following:

basic=true | false

when set to True, produces a table that provides the basic optimization history.

Default	true

estimatesForEachStep=true | false

when set to True, produces a table that provides the parameter estimates calculated at each iteration during the optimization process.

Default	false

olsEstimates=true | false

Default	false

maxf=double

specifies the maximum number of objective function evaluations in the optimization process.

Minimum value	0

maxit=double

specifies the maximum number of iterations in the optimization process.

Alias	maxiter
Minimum value	0

maxtime=double

specifies an upper limit (in seconds) on the CPU time for the optimization process.

Minimum value	0

sing=double

specifies the singularity criterion to use for the inversion of the Hessian matrix.

Minimum value	0

sweepSing=double

specifies the singularity criterion to use for the inversion of the SSCP matrix.

Minimum value	0

output={spregoutputStatement}

specifies details for an output data table to contain scores for various statistics.

The spregoutputStatement value can be one or more of the following:

* casOut={casouttable}

specifies the settings for an output table.

For more information about specifying the casOut parameter, see the common casouttable parameter (Appendix A: Common Parameters).

copyVars="ALL" | "ALL_MODEL" | "ALL_NUMERIC" | {"variable-name-1" <, "variable-name-2", ...>}

pred="string"

names the variable to contain the expected value of the response variable.

Aliases	expected
Aliases	mean

resid="string"

names the variable to contain the residual.

Alias	residual

xbeta="string"

names the variable to contain the estimates of xbeta.

Alias	xb

outputTables={outputTables}

specifies the list of display tables that you want to output as CAS tables. If this parameter is not specified, no tables are output as CAS tables.

For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).

Alias	displayOut

restrictions={"string-1" <, "string-2", ...>}

specifies linear restrictions to be imposed on the parameter estimates.

spatialeffects={slxmodelstmt}

specifies independent regressor variables whose spatial lag is to be added to the MODEL statement.

The slxmodelstmt value can be one or more of the following:

depVars={{responsevar-1} <, {responsevar-2}, ...>}

specifies one or more variables to use as response variables in the model. Not all models support more than one response variable.

Aliases	depVar
Aliases	target

name="variable-name"

names the response variable.

effects={{effect-1} <, {effect-2}, ...>}

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Alias	interact
Default	NONE

maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

nest={"string-1" <, "string-2", ...>}

* vars={"string-1" <, "string-2", ...>}

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

spatialid="variable-name"

specifies a variable that identifies an observation in two tables of input data and spatial weights.

Alias	sid

* table={castable}

specifies the input data table.

For more information about specifying the table parameter, see the common castable parameter (Appendix A: Common Parameters).

tests={{singleTest-1} <, {singleTest-2}, ...>}

specifies linear hypotheses about the regression parameters that are specified in the model and tests to be performed on the hypotheses (Wald, Lagrange multiplier, and likelihood ratio tests).

The singleTest value can be one or more of the following:

* eqns={"string-1" <, "string-2", ...>}

specifies a list of equations to be tested for a single test.

testLabel="string"

specifies a label to be assigned to a single test.

testNames={"string-1" <, "string-2", ...>}

specifies one or more of the tests (Wald, LM, and LR) to be applied to each equation in the list.

Default	WALD

timingReport={timingReportOpts}

specifies the type of timing information that you want the action to provide.

The timingReportOpts value can be one or more of the following:

details=true | false

when set to True, produces a detailed summary of the time used for all phases of execution.

Default	false

summary=true | false

when set to True, produces a summary of the time used for the main phases of execution.

Default	false

wmatrix={castable}

specifies the input table of spatial weights.

For more information about specifying the wmatrix parameter, see the common castable parameter (Appendix A: Common Parameters).

Alias	wmat

spatialreg Action

Analyzes regression models for spatial data.

Python Syntax

results= s.spatialreg.spatialreg(

bounds=["string-1" <, "string-2", ...>],

class_=[{

"countMissing":True | False,

"descending":True | False,

"ignoreMissing":True | False,

"maxLev":integer,

"order":"FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL",

"ref":"FIRST" | "LAST" | double | "string",

"vars":["variable-name-1" <, "variable-name-2", ...>]

}<, {...}>],

display={

"caseSensitive":True | False,

"exclude":True | False,

"excludeAll":True | False,

"keyIsPath":True | False,

"names":["string-1" <, "string-2", ...>],

"pathType":"LABEL" | "NAME",

"traceNames":True | False

impact={

"nmc":integer,

"order":integer,

"seed":integer

includeinternalnames=True | False,

initialvalues=["string-1" <, "string-2", ...>],

model={

"depVars":[{

"name":"variable-name"

}<, {...}>],

"effects":[{

"interaction":"BAR" | "CROSS" | "NONE",

"maxInteract":integer,

"nest":["string-1" <, "string-2", ...>],

"vars":["string-1" <, "string-2", ...>]

}<, {...}>],

"modeloptions":{

"corrb":True | False

"covb":True | False

"modelLabel":"string"

"modeltype":"ALL" | "AUTO" | "CAR" | "LINEAR" | "SAC" | "SAR" | "SARMA" | "SEM" | "SMA"

"noint":True | False

montecarloapprox={

"method":"CHEBYSHEV" | "TAYLOR",

"nmc":integer,

"order":integer,

"seed":integer

nonormalizeWMatrix=True | False,

optimizer={

"aftl":double,

"agtl":double,

"atol":double,

"axtl":double,

"ceps":double,

"covestmethod":"CROSSOP" | "HESSIAN" | "QML",

"ftol":double,

"gtol":double,

"iterationHistory":{

"basic":True | False

"estimatesForEachStep":True | False

"olsEstimates":True | False

"maxf":double,

"maxit":double,

"maxtime":double,

"sing":double,

"sweepSing":double

output={

"casOut":{

"caslib":"string"

"compress":True | False

"indexVars":["variable-name-1" <, "variable-name-2", ...>]

"label":"string"

"lifetime":64-bit-integer

"maxMemSize":64-bit-integer

"memoryFormat":"DVR" | "INHERIT" | "STANDARD"

"name":"table-name"

"onDemand":True | False

"promote":True | False

"replace":True | False

"replication":integer

"threadBlockSize":64-bit-integer

"timeStamp":"string"

"where":["string-1" <, "string-2", ...>]

"copyVars":"ALL" | "ALL_MODEL" | "ALL_NUMERIC" | ["variable-name-1" <, "variable-name-2", ...>],

"pred":"string",

"resid":"string",

"xbeta":"string"

outputTables={

"groupByVarsRaw":True | False,

"includeAll":True | False,

"names":["string-1" <, "string-2", ...>] | {"key-1":{casouttable-1} <, "key-2":{casouttable-2}, ...>},

"repeated":True | False,

"replace":True | False

restrictions=["string-1" <, "string-2", ...>],

spatialeffects={

"depVars":[{

"name":"variable-name"

}<, {...}>],

"effects":[{

"interaction":"BAR" | "CROSS" | "NONE",

"maxInteract":integer,

"nest":["string-1" <, "string-2", ...>],

"vars":["string-1" <, "string-2", ...>]

}<, {...}>]

spatialid="variable-name",

table={

"caslib":"string",

"computedOnDemand":True | False,

"computedVars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"computedVarsProgram":"string",

"dataSourceOptions":{"key-1":{any-list-or-data-type-1} <, "key-2":{any-list-or-data-type-2}, ...>},

"groupBy":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"groupByMode":"NOSORT" | "REDISTRIBUTE",

"importOptions":{"fileType":"ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DELIMITED" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SOUND" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters},

"name":"table-name",

"onDemand":True | False,

"orderBy":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"singlePass":True | False,

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"where":"where-expression",

"whereTable":{

"casLib":"string"

"dataSourceOptions":{adls_noreq-parameters | bigquery-parameters | cas_noreq-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | fedsvr-parameters | gcs_noreq-parameters | hadoop-parameters | hana-parameters | impala-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sforce-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

"name":"table-name"

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>]

"where":"where-expression"

}

tests=[{

"eqns":["string-1" <, "string-2", ...>],

"testLabel":"string",

"testNames":["string-1" <, "string-2", ...>]

}<, {...}>],

timingReport={

"details":True | False,

"summary":True | False

wmatrix={

"caslib":"string",

"computedOnDemand":True | False,

"computedVars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"computedVarsProgram":"string",

"dataSourceOptions":{"key-1":{any-list-or-data-type-1} <, "key-2":{any-list-or-data-type-2}, ...>},

"groupBy":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"groupByMode":"NOSORT" | "REDISTRIBUTE",

"name":"table-name",

"onDemand":True | False,

"orderBy":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"singlePass":True | False,

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"where":"where-expression",

"whereTable":{

"casLib":"string"

"name":"table-name"

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>]

"where":"where-expression"

}

)

indicates a required parameter

Summary: Input and Output Tables

If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
required parametertable	—	specifies the input data table.
wmatrix	—	specifies the input table of spatial weights.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
output	required parametercasOut	specifies details for an output data table to contain scores for various statistics.
outputTables	names	specifies the list of display tables that you want to output as CAS tables. If this parameter is not specified, no tables are output as CAS tables.

Parameter Descriptions

bounds=["string-1" <, "string-2", ...>]

imposes simple boundary constraints on the parameter estimates.

class_=[{classStatement-1} <, {classStatement-2}, ...>]

specifies the classification variables.

Alias	classVars

The classStatement value can be one or more of the following:

"countMissing":True | False

when set to True, treats missing as a valid level for this variable.

Default	False

"descending":True | False

when set to True, reverses the sort order that is imposed by the order parameter.

Default	False

"ignoreMissing":True | False

when set to True, ignores the fact that some variables in the observation have missing values and honors the nonmissing values for other variables in that observation.

Default	False

"maxLev":integer

specifies the maximum number of levels. A value of 0 means an unlimited number of levels.

Default	0
Minimum value	0

"order":"FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL"

specifies the sort order for the levels of the classification variable. This ordering determines which parameters in the model correspond to each level in the data.

"param":"BTH" | "EFFECT" | "GLM" | "ORDINAL" | "ORTHBTH" | "ORTHEFFECT" | "ORTHORDINAL" | "ORTHPOLY" | "ORTHREF" | "POLYNOMIAL" | "REFERENCE"

"ref":"FIRST" | "LAST" | double | "string"

* "vars":["variable-name-1" <, "variable-name-2", ...>]

specifies the classification variables.

Alias	name

display={displayTables}

specifies the list of display tables that you want the action to create. If this parameter is not specified, all tables are created.

For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).

impact={ImpactEstOptions}

specifies impact estimation control options.

Alias	impactestimate

The ImpactEstOptions value can be one or more of the following:

"nmc":integer

specifies the number of random draws for impact estimation.

Alias	ndraws
Minimum value	1

"order":integer

specifies the order of Neumann series for impact estimation.

Alias	truncorder
Range	1–2000

"seed":integer

specifies the seed for random number generation for impact estimation.

Alias	randomseed
Minimum value	1

includeinternalnames=True | False

when set to True, adds an extra column to the parameter estimates table that shows the internal names for the parameters.

Default	False

initialvalues=["string-1" <, "string-2", ...>]

specifies initial values for parameters in the optimization.

* model={spregmodelstmt}

specifies the dependent variable and independent regressor variables for the regression model.

The spregmodelstmt value can be one or more of the following:

"depVars":[{responsevar-1} <, {responsevar-2}, ...>]

specifies one or more variables to use as response variables in the model. Not all models support more than one response variable.

Aliases	depVar
Aliases	target

"name":"variable-name"

names the response variable.

"effects":[{effect-1} <, {effect-2}, ...>]

The effect value can be one or more of the following:

"interaction":"BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Alias	interact
Default	NONE

"maxInteract":integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

"nest":["string-1" <, "string-2", ...>]

* "vars":["string-1" <, "string-2", ...>]

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

"modeloptions":{modeloptions}

specifies options that you can apply to the model.

The modeloptions value can be one or more of the following:

"corrb":True | False

when set to True, produces a table of the correlations of the parameter estimates.

Default	False

"covb":True | False

when set to True, produces a table of the covariances of the parameter estimates.

Default	False

"modelLabel":"string"

specifies a label for the model.

"modeltype":"ALL" | "AUTO" | "CAR" | "LINEAR" | "SAC" | "SAR" | "SARMA" | "SEM" | "SMA"

specifies the type of model to be analyzed.

Default	SAR

ALL

analyzes all supported models

AUTO

analyzes selected multiple models

CAR

analyzes a conditional autoregressive model.

LINEAR

analyzes a linear model.

SAC

analyzes a spatial autoregressive confused model.

SAR

analyzes a spatial autoregressive model.

SARMA

analyzes a spatial autoregressive moving average model.

SEM

analyzes a spatial error model.

SMA

analyzes a spatial moving average model.

"noint":True | False

when set to True, suppresses the intercept parameter.

Default	False

"noint":True | False

when set to True, does not include the intercept term in the model.

Default	False

montecarloapprox={MCApproxOptions}

specifies Monte Carlo approximation control options.

Alias	approximation

Long form	montecarloapprox={"method":"CHEBYSHEV" \| "TAYLOR"}
Shortcut form	montecarloapprox="CHEBYSHEV" \| "TAYLOR"

The MCApproxOptions value can be one or more of the following:

"method":"CHEBYSHEV" | "TAYLOR"

specifies the type of approximation to use.

Alias	approxmethod
Default	CHEBYSHEV

"nmc":integer

specifies the number of random draws for approximation.

Alias	ndraws
Minimum value	1

"order":integer

specifies the order of series in the Taylor or Chebyshev approximation.

Alias	truncorder
Range	1–2000

"seed":integer

specifies the seed for random number generation.

Alias	randomseed
Minimum value	1

nonormalizeWMatrix=True | False

when set to True, suppresses the row standardization of the spatial weights matrix.

Default	False

optimizer={optimizerOpts}

specifies parameters that control various aspects of the parameter estimation process.

Long form	optimizer={"algorithm":"CONJUGATEGRADIENT" \| "DOUBLEDOGLEG" \| "NEWTONRAPHSONWITHLINESEARCH" \| "NEWTONRAPHSONWITHRIDGING" \| "NONE" \| "QUASINEWTON" \| "TRUSTREGION"}
Shortcut form	optimizer="CONJUGATEGRADIENT" \| "DOUBLEDOGLEG" \| "NEWTONRAPHSONWITHLINESEARCH" \| "NEWTONRAPHSONWITHRIDGING" \| "NONE" \| "QUASINEWTON" \| "TRUSTREGION"

The optimizerOpts value can be one or more of the following:

"aftl":double

specifies an absolute function difference convergence criterion.

Aliases	absfconv
Aliases	absftol
Minimum value	0

"agtl":double

specifies an absolute gradient convergence criterion.

Aliases	absgconv
Aliases	absgtol
Minimum value	0

"algorithm":"CONJUGATEGRADIENT" | "DOUBLEDOGLEG" | "NEWTONRAPHSONWITHLINESEARCH" | "NEWTONRAPHSONWITHRIDGING" | "NONE" | "QUASINEWTON" | "TRUSTREGION"

specifies the nonlinear optimization technique to use.

Aliases	technique
	tech
	method
Default	NEWTONRAPHSONWITHLINESEARCH

"atol":double

specifies an absolute function convergence criterion.

"axtl":double

specifies an absolute parameter convergence criterion.

Alias	absxconv
Minimum value	0

"ceps":double

specifies the infeasibility tolerance applied to constraints (such as restrictions and bounds).

Aliases	lceps
Aliases	feastol
Minimum value	0

"covestmethod":"CROSSOP" | "HESSIAN" | "QML"

specifies the covariance estimation method to use.

Alias	covest
Default	HESSIAN

CROSSOP

specifies the covariance from the outer product matrix.

HESSIAN

specifies the covariance from the Hessian matrix.

QML

specifies the covariance from the outer product and Hessian matrix.

"ftol":double

specifies a relative function difference convergence criterion.

Alias	fconv
Minimum value	0

"gtol":double

specifies a relative gradient convergence criterion.

Alias	gconv
Minimum value	0

"iterationHistory":{iterationHistoryOpts}

when set to True, produces various tables that describe the iteration process.

The iterationHistoryOpts value can be one or more of the following:

"basic":True | False

when set to True, produces a table that provides the basic optimization history.

Default	True

"estimatesForEachStep":True | False

when set to True, produces a table that provides the parameter estimates calculated at each iteration during the optimization process.

Default	False

"olsEstimates":True | False

Default	False

"maxf":double

specifies the maximum number of objective function evaluations in the optimization process.

Minimum value	0

"maxit":double

specifies the maximum number of iterations in the optimization process.

Alias	maxiter
Minimum value	0

"maxtime":double

specifies an upper limit (in seconds) on the CPU time for the optimization process.

Minimum value	0

"sing":double

specifies the singularity criterion to use for the inversion of the Hessian matrix.

Minimum value	0

"sweepSing":double

specifies the singularity criterion to use for the inversion of the SSCP matrix.

Minimum value	0

output={spregoutputStatement}

specifies details for an output data table to contain scores for various statistics.

The spregoutputStatement value can be one or more of the following:

* "casOut":{casouttable}

specifies the settings for an output table.

For more information about specifying the casOut parameter, see the common casouttable parameter (Appendix A: Common Parameters).

"copyVars":"ALL" | "ALL_MODEL" | "ALL_NUMERIC" | ["variable-name-1" <, "variable-name-2", ...>]

"pred":"string"

names the variable to contain the expected value of the response variable.

Aliases	expected
Aliases	mean

"resid":"string"

names the variable to contain the residual.

Alias	residual

"xbeta":"string"

names the variable to contain the estimates of xbeta.

Alias	xb

outputTables={outputTables}

specifies the list of display tables that you want to output as CAS tables. If this parameter is not specified, no tables are output as CAS tables.

For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).

Alias	displayOut

restrictions=["string-1" <, "string-2", ...>]

specifies linear restrictions to be imposed on the parameter estimates.

spatialeffects={slxmodelstmt}

specifies independent regressor variables whose spatial lag is to be added to the MODEL statement.

The slxmodelstmt value can be one or more of the following:

"depVars":[{responsevar-1} <, {responsevar-2}, ...>]

specifies one or more variables to use as response variables in the model. Not all models support more than one response variable.

Aliases	depVar
Aliases	target

"name":"variable-name"

names the response variable.

"effects":[{effect-1} <, {effect-2}, ...>]

The effect value can be one or more of the following:

"interaction":"BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Alias	interact
Default	NONE

"maxInteract":integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

"nest":["string-1" <, "string-2", ...>]

* "vars":["string-1" <, "string-2", ...>]

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

spatialid="variable-name"

specifies a variable that identifies an observation in two tables of input data and spatial weights.

Alias	sid

* table={castable}

specifies the input data table.

For more information about specifying the table parameter, see the common castable parameter (Appendix A: Common Parameters).

tests=[{singleTest-1} <, {singleTest-2}, ...>]

specifies linear hypotheses about the regression parameters that are specified in the model and tests to be performed on the hypotheses (Wald, Lagrange multiplier, and likelihood ratio tests).

The singleTest value can be one or more of the following:

* "eqns":["string-1" <, "string-2", ...>]

specifies a list of equations to be tested for a single test.

"testLabel":"string"

specifies a label to be assigned to a single test.

"testNames":["string-1" <, "string-2", ...>]

specifies one or more of the tests (Wald, LM, and LR) to be applied to each equation in the list.

Default	WALD

timingReport={timingReportOpts}

specifies the type of timing information that you want the action to provide.

The timingReportOpts value can be one or more of the following:

"details":True | False

when set to True, produces a detailed summary of the time used for all phases of execution.

Default	False

"summary":True | False

when set to True, produces a summary of the time used for the main phases of execution.

Default	False

wmatrix={castable}

specifies the input table of spatial weights.

For more information about specifying the wmatrix parameter, see the common castable parameter (Appendix A: Common Parameters).

Alias	wmat

spatialreg Action

Analyzes regression models for spatial data.

R Syntax

results <– cas.spatialreg.spatialreg(s,

bounds=list("string-1" <, "string-2", ...>),

class=list( list(

countMissing=TRUE | FALSE,

descending=TRUE | FALSE,

ignoreMissing=TRUE | FALSE,

maxLev=integer,

order="FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL",

ref="FIRST" | "LAST" | double | "string",

vars=list("variable-name-1" <, "variable-name-2", ...>)

) <, list(...)>),

display=list(

caseSensitive=TRUE | FALSE,

exclude=TRUE | FALSE,

excludeAll=TRUE | FALSE,

keyIsPath=TRUE | FALSE,

names=list("string-1" <, "string-2", ...>),

pathType="LABEL" | "NAME",

traceNames=TRUE | FALSE

impact=list(

nmc=integer,

order=integer,

seed=integer

includeinternalnames=TRUE | FALSE,

initialvalues=list("string-1" <, "string-2", ...>),

model=list(

depVars=list( list(

name="variable-name"

) <, list(...)>),

effects=list( list(

interaction="BAR" | "CROSS" | "NONE",

maxInteract=integer,

nest=list("string-1" <, "string-2", ...>),

vars=list("string-1" <, "string-2", ...>)

) <, list(...)>),

modeloptions=list(

corrb=TRUE | FALSE

covb=TRUE | FALSE

modelLabel="string"

modeltype="ALL" | "AUTO" | "CAR" | "LINEAR" | "SAC" | "SAR" | "SARMA" | "SEM" | "SMA"

noint=TRUE | FALSE

montecarloapprox=list(

method="CHEBYSHEV" | "TAYLOR",

nmc=integer,

order=integer,

seed=integer

nonormalizeWMatrix=TRUE | FALSE,

optimizer=list(

aftl=double,

agtl=double,

atol=double,

axtl=double,

ceps=double,

covestmethod="CROSSOP" | "HESSIAN" | "QML",

ftol=double,

gtol=double,

iterationHistory=list(

basic=TRUE | FALSE

estimatesForEachStep=TRUE | FALSE

olsEstimates=TRUE | FALSE

maxf=double,

maxit=double,

maxtime=double,

sing=double,

sweepSing=double

output=list(

casOut=list(

caslib="string"

compress=TRUE | FALSE

indexVars=list("variable-name-1" <, "variable-name-2", ...>)

label="string"

lifetime=64-bit-integer

maxMemSize=64-bit-integer

memoryFormat="DVR" | "INHERIT" | "STANDARD"

name="table-name"

onDemand=TRUE | FALSE

promote=TRUE | FALSE

replace=TRUE | FALSE

replication=integer

threadBlockSize=64-bit-integer

timeStamp="string"

where=list("string-1" <, "string-2", ...>)

copyVars="ALL" | "ALL_MODEL" | "ALL_NUMERIC" | list("variable-name-1" <, "variable-name-2", ...>),

pred="string",

resid="string",

xbeta="string"

outputTables=list(

groupByVarsRaw=TRUE | FALSE,

includeAll=TRUE | FALSE,

names=list("string-1" <, "string-2", ...>) | list(key-1=list(casouttable-1) <, key-2=list(casouttable-2), ...>),

repeated=TRUE | FALSE,

replace=TRUE | FALSE

restrictions=list("string-1" <, "string-2", ...>),

spatialeffects=list(

depVars=list( list(

name="variable-name"

) <, list(...)>),

effects=list( list(

interaction="BAR" | "CROSS" | "NONE",

maxInteract=integer,

nest=list("string-1" <, "string-2", ...>),

vars=list("string-1" <, "string-2", ...>)

) <, list(...)>)

spatialid="variable-name",

table=list(

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

computedVarsProgram="string",

dataSourceOptions=list(key-1=list(any-list-or-data-type-1) <, key-2=list(any-list-or-data-type-2), ...>),

groupBy=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

onDemand=TRUE | FALSE,

orderBy=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

singlePass=TRUE | FALSE,

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

where="where-expression",

whereTable=list(

casLib="string"

name="table-name"

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>)

where="where-expression"

)

tests=list( list(

eqns=list("string-1" <, "string-2", ...>),

testLabel="string",

testNames=list("string-1" <, "string-2", ...>)

) <, list(...)>),

timingReport=list(

details=TRUE | FALSE,

summary=TRUE | FALSE

wmatrix=list(

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

computedVarsProgram="string",

dataSourceOptions=list(key-1=list(any-list-or-data-type-1) <, key-2=list(any-list-or-data-type-2), ...>),

groupBy=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

onDemand=TRUE | FALSE,

orderBy=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

singlePass=TRUE | FALSE,

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

where="where-expression",

whereTable=list(

casLib="string"

name="table-name"

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>)

where="where-expression"

)

indicates a required parameter

Summary: Input and Output Tables

If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
required parametertable	—	specifies the input data table.
wmatrix	—	specifies the input table of spatial weights.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
output	required parametercasOut	specifies details for an output data table to contain scores for various statistics.
outputTables	names	specifies the list of display tables that you want to output as CAS tables. If this parameter is not specified, no tables are output as CAS tables.

Parameter Descriptions

bounds=list("string-1" <, "string-2", ...>)

imposes simple boundary constraints on the parameter estimates.

class=list( list(classStatement-1) <, list(classStatement-2), ...>)

specifies the classification variables.

Alias	classVars

The classStatement value can be one or more of the following:

countMissing=TRUE | FALSE

when set to True, treats missing as a valid level for this variable.

Default	FALSE

descending=TRUE | FALSE

when set to True, reverses the sort order that is imposed by the order parameter.

Default	FALSE

ignoreMissing=TRUE | FALSE

when set to True, ignores the fact that some variables in the observation have missing values and honors the nonmissing values for other variables in that observation.

Default	FALSE

maxLev=integer

specifies the maximum number of levels. A value of 0 means an unlimited number of levels.

Default	0
Minimum value	0

order="FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL"

specifies the sort order for the levels of the classification variable. This ordering determines which parameters in the model correspond to each level in the data.

param="BTH" | "EFFECT" | "GLM" | "ORDINAL" | "ORTHBTH" | "ORTHEFFECT" | "ORTHORDINAL" | "ORTHPOLY" | "ORTHREF" | "POLYNOMIAL" | "REFERENCE"

ref="FIRST" | "LAST" | double | "string"

* vars=list("variable-name-1" <, "variable-name-2", ...>)

specifies the classification variables.

Alias	name

display=list(displayTables)

specifies the list of display tables that you want the action to create. If this parameter is not specified, all tables are created.

For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).

impact=list(ImpactEstOptions)

specifies impact estimation control options.

Alias	impactestimate

The ImpactEstOptions value can be one or more of the following:

nmc=integer

specifies the number of random draws for impact estimation.

Alias	ndraws
Minimum value	1

order=integer

specifies the order of Neumann series for impact estimation.

Alias	truncorder
Range	1–2000

seed=integer

specifies the seed for random number generation for impact estimation.

Alias	randomseed
Minimum value	1

includeinternalnames=TRUE | FALSE

when set to True, adds an extra column to the parameter estimates table that shows the internal names for the parameters.

Default	FALSE

initialvalues=list("string-1" <, "string-2", ...>)

specifies initial values for parameters in the optimization.

* model=list(spregmodelstmt)

specifies the dependent variable and independent regressor variables for the regression model.

The spregmodelstmt value can be one or more of the following:

depVars=list( list(responsevar-1) <, list(responsevar-2), ...>)

specifies one or more variables to use as response variables in the model. Not all models support more than one response variable.

Aliases	depVar
Aliases	target

name="variable-name"

names the response variable.

effects=list( list(effect-1) <, list(effect-2), ...>)

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Alias	interact
Default	NONE

maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

nest=list("string-1" <, "string-2", ...>)

* vars=list("string-1" <, "string-2", ...>)

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

modeloptions=list(modeloptions)

specifies options that you can apply to the model.

The modeloptions value can be one or more of the following:

corrb=TRUE | FALSE

when set to True, produces a table of the correlations of the parameter estimates.

Default	FALSE

covb=TRUE | FALSE

when set to True, produces a table of the covariances of the parameter estimates.

Default	FALSE

modelLabel="string"

specifies a label for the model.

modeltype="ALL" | "AUTO" | "CAR" | "LINEAR" | "SAC" | "SAR" | "SARMA" | "SEM" | "SMA"

specifies the type of model to be analyzed.

Default	SAR

ALL

analyzes all supported models

AUTO

analyzes selected multiple models

CAR

analyzes a conditional autoregressive model.

LINEAR

analyzes a linear model.

SAC

analyzes a spatial autoregressive confused model.

SAR

analyzes a spatial autoregressive model.

SARMA

analyzes a spatial autoregressive moving average model.

SEM

analyzes a spatial error model.

SMA

analyzes a spatial moving average model.

noint=TRUE | FALSE

when set to True, suppresses the intercept parameter.

Default	FALSE

noint=TRUE | FALSE

when set to True, does not include the intercept term in the model.

Default	FALSE

montecarloapprox=list(MCApproxOptions)

specifies Monte Carlo approximation control options.

Alias	approximation

Long form	montecarloapprox=list(method="CHEBYSHEV" \| "TAYLOR")
Shortcut form	montecarloapprox="CHEBYSHEV" \| "TAYLOR"

The MCApproxOptions value can be one or more of the following:

method="CHEBYSHEV" | "TAYLOR"

specifies the type of approximation to use.

Alias	approxmethod
Default	CHEBYSHEV

nmc=integer

specifies the number of random draws for approximation.

Alias	ndraws
Minimum value	1

order=integer

specifies the order of series in the Taylor or Chebyshev approximation.

Alias	truncorder
Range	1–2000

seed=integer

specifies the seed for random number generation.

Alias	randomseed
Minimum value	1

nonormalizeWMatrix=TRUE | FALSE

when set to True, suppresses the row standardization of the spatial weights matrix.

Default	FALSE

optimizer=list(optimizerOpts)

specifies parameters that control various aspects of the parameter estimation process.

Long form	optimizer=list(algorithm="CONJUGATEGRADIENT" \| "DOUBLEDOGLEG" \| "NEWTONRAPHSONWITHLINESEARCH" \| "NEWTONRAPHSONWITHRIDGING" \| "NONE" \| "QUASINEWTON" \| "TRUSTREGION")
Shortcut form	optimizer="CONJUGATEGRADIENT" \| "DOUBLEDOGLEG" \| "NEWTONRAPHSONWITHLINESEARCH" \| "NEWTONRAPHSONWITHRIDGING" \| "NONE" \| "QUASINEWTON" \| "TRUSTREGION"

The optimizerOpts value can be one or more of the following:

aftl=double

specifies an absolute function difference convergence criterion.

Aliases	absfconv
Aliases	absftol
Minimum value	0

agtl=double

specifies an absolute gradient convergence criterion.

Aliases	absgconv
Aliases	absgtol
Minimum value	0

algorithm="CONJUGATEGRADIENT" | "DOUBLEDOGLEG" | "NEWTONRAPHSONWITHLINESEARCH" | "NEWTONRAPHSONWITHRIDGING" | "NONE" | "QUASINEWTON" | "TRUSTREGION"

specifies the nonlinear optimization technique to use.

Aliases	technique
	tech
	method
Default	NEWTONRAPHSONWITHLINESEARCH

atol=double

specifies an absolute function convergence criterion.

axtl=double

specifies an absolute parameter convergence criterion.

Alias	absxconv
Minimum value	0

ceps=double

specifies the infeasibility tolerance applied to constraints (such as restrictions and bounds).

Aliases	lceps
Aliases	feastol
Minimum value	0

covestmethod="CROSSOP" | "HESSIAN" | "QML"

specifies the covariance estimation method to use.

Alias	covest
Default	HESSIAN

CROSSOP

specifies the covariance from the outer product matrix.

HESSIAN

specifies the covariance from the Hessian matrix.

QML

specifies the covariance from the outer product and Hessian matrix.

ftol=double

specifies a relative function difference convergence criterion.

Alias	fconv
Minimum value	0

gtol=double

specifies a relative gradient convergence criterion.

Alias	gconv
Minimum value	0

iterationHistory=list(iterationHistoryOpts)

when set to True, produces various tables that describe the iteration process.

The iterationHistoryOpts value can be one or more of the following:

basic=TRUE | FALSE

when set to True, produces a table that provides the basic optimization history.

Default	TRUE

estimatesForEachStep=TRUE | FALSE

when set to True, produces a table that provides the parameter estimates calculated at each iteration during the optimization process.

Default	FALSE

olsEstimates=TRUE | FALSE

Default	FALSE

maxf=double

specifies the maximum number of objective function evaluations in the optimization process.

Minimum value	0

maxit=double

specifies the maximum number of iterations in the optimization process.

Alias	maxiter
Minimum value	0

maxtime=double

specifies an upper limit (in seconds) on the CPU time for the optimization process.

Minimum value	0

sing=double

specifies the singularity criterion to use for the inversion of the Hessian matrix.

Minimum value	0

sweepSing=double

specifies the singularity criterion to use for the inversion of the SSCP matrix.

Minimum value	0

output=list(spregoutputStatement)

specifies details for an output data table to contain scores for various statistics.

The spregoutputStatement value can be one or more of the following:

* casOut=list(casouttable)

specifies the settings for an output table.

For more information about specifying the casOut parameter, see the common casouttable parameter (Appendix A: Common Parameters).

copyVars="ALL" | "ALL_MODEL" | "ALL_NUMERIC" | list("variable-name-1" <, "variable-name-2", ...>)

pred="string"

names the variable to contain the expected value of the response variable.

Aliases	expected
Aliases	mean

resid="string"

names the variable to contain the residual.

Alias	residual

xbeta="string"

names the variable to contain the estimates of xbeta.

Alias	xb

outputTables=list(outputTables)

specifies the list of display tables that you want to output as CAS tables. If this parameter is not specified, no tables are output as CAS tables.

For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).

Alias	displayOut

restrictions=list("string-1" <, "string-2", ...>)

specifies linear restrictions to be imposed on the parameter estimates.

spatialeffects=list(slxmodelstmt)

specifies independent regressor variables whose spatial lag is to be added to the MODEL statement.

The slxmodelstmt value can be one or more of the following:

depVars=list( list(responsevar-1) <, list(responsevar-2), ...>)

specifies one or more variables to use as response variables in the model. Not all models support more than one response variable.

Aliases	depVar
Aliases	target

name="variable-name"

names the response variable.

effects=list( list(effect-1) <, list(effect-2), ...>)

The effect value can be one or more of the following:

interaction="BAR" | "CROSS" | "NONE"

specifies the type of interaction for the variables.

Alias	interact
Default	NONE

maxInteract=integer

eliminates interaction effects whose order is higher than the specified integer value when used in conjunction with the BAR interaction.

nest=list("string-1" <, "string-2", ...>)

* vars=list("string-1" <, "string-2", ...>)

specifies the variables to use in defining a term of the effect. You must specify at least one variable.

spatialid="variable-name"

specifies a variable that identifies an observation in two tables of input data and spatial weights.

Alias	sid

* table=list(castable)

specifies the input data table.

For more information about specifying the table parameter, see the common castable parameter (Appendix A: Common Parameters).

tests=list( list(singleTest-1) <, list(singleTest-2), ...>)

specifies linear hypotheses about the regression parameters that are specified in the model and tests to be performed on the hypotheses (Wald, Lagrange multiplier, and likelihood ratio tests).

The singleTest value can be one or more of the following:

* eqns=list("string-1" <, "string-2", ...>)

specifies a list of equations to be tested for a single test.

testLabel="string"

specifies a label to be assigned to a single test.

testNames=list("string-1" <, "string-2", ...>)

specifies one or more of the tests (Wald, LM, and LR) to be applied to each equation in the list.

Default	WALD

timingReport=list(timingReportOpts)

specifies the type of timing information that you want the action to provide.

The timingReportOpts value can be one or more of the following:

details=TRUE | FALSE

when set to True, produces a detailed summary of the time used for all phases of execution.

Default	FALSE

summary=TRUE | FALSE

when set to True, produces a summary of the time used for the main phases of execution.

Default	FALSE

wmatrix=list(castable)

specifies the input table of spatial weights.

For more information about specifying the wmatrix parameter, see the common castable parameter (Appendix A: Common Parameters).

Alias	wmat

Last updated: June 22, 2022