Regression Action Set

Provides actions for fitting linear, generalized linear, and logistic models

modelMatrix Action

creates a table on the server that contains the design matrix associated with a given model statement..

CASL Syntax

regression.modelMatrix <result=results> <status=rc> /
attributes={{
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
}, {...}},
class={{
countMissing=TRUE | FALSE,
descending=TRUE | FALSE,
ignoreMissing=TRUE | FALSE,
levelizeRaw=TRUE | FALSE,
maxLev=integer,
order="FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL",
param="BTH" | "EFFECT" | "GLM" | "ORDINAL" | "ORTHBTH" | "ORTHEFFECT" | "ORTHORDINAL" | "ORTHPOLY" | "ORTHREF" | "POLYNOMIAL" | "REFERENCE",
ref="FIRST" | "LAST" | double | "string",
split=TRUE | FALSE,
required parameter vars={"variable-name-1" <, "variable-name-2", ...>}
}, {...}},
collection={{
details=TRUE | FALSE,
required parameter name="string",
required parameter 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
},
freq="variable-name",
inputs={{
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
}, {...}},
model={
depVars={{
name="variable-name"
}, {...}},
effects={{
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest={"string-1" <, "string-2", ...>},
required parameter vars={"string-1" <, "string-2", ...>}
}, {...}},
entry="variable-name",
group={{
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest={"string-1" <, "string-2", ...>},
required parameter vars={"string-1" <, "string-2", ...>}
}, {...}},
include=integer | {{effect-1} <, {effect-2}, ...>},
informative=TRUE | FALSE,
noint=TRUE | FALSE,
start=integer | {{effect-1} <, {effect-2}, ...>}
},
multimember={{
details=TRUE | FALSE,
required parameter name="string",
noEffect=TRUE | FALSE,
stdize=TRUE | FALSE,
required parameter vars={"variable-name-1" <, "variable-name-2", ...>},
weight={"variable-name-1" <, "variable-name-2", ...>}
}, {...}},
nominals={{
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
}, {...}},
required parameter output={
required parameter 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"
promote=TRUE | FALSE
replace=TRUE | FALSE
replication=integer
tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE"
threadBlockSize=64-bit-integer
timeStamp="string"
where={"string-1" <, "string-2", ...>}
},
copyVars="ALL" | "ALL_MODEL" | "ALL_NUMERIC" | {"variable-name-1" <, "variable-name-2", ...>},
prefix="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
},
polynomial={{
degree=integer,
details=TRUE | FALSE,
labelStyle={
expand=TRUE | FALSE
exponent="string"
includeName=TRUE | FALSE
productSymbol="NONE" | "string"
},
mDegree=integer,
required parameter name="string",
noSeparate=TRUE | FALSE,
standardize={
method="MOMENTS" | "MRANGE" | "WMOMENTS"
options="CENTER" | "CENTERSCALE" | "NONE" | "SCALE"
prefix="NONE" | "string"
},
required parameter vars={"variable-name-1" <, "variable-name-2", ...>}
}, {...}},
spline={{
basis="BSPLINE" | "TPF_DEFAULT" | "TPF_NOINT" | "TPF_NOINTANDNOPOWERS" | "TPF_NOPOWERS",
dataBoundary=TRUE | FALSE,
degree=integer,
details=TRUE | FALSE,
knotMax=double,
knotMethod={
equal=integer
list={double-1 <, double-2, ...>}
listWithBoundary={double-1 <, double-2, ...>}
multiscale={
endScale=integer
startScale=integer
}
rangeFractions={double-1 <, double-2, ...>}
},
knotMin=double,
required parameter name="string",
naturalCubic=TRUE | FALSE,
separate=TRUE | FALSE,
split=TRUE | FALSE,
required parameter vars={"variable-name-1" <, "variable-name-2", ...>}
}, {...}},
required parameter table={
caslib="string",
computedOnDemand=TRUE | FALSE,
computedVars={{
format="string",
formattedLength=integer,
label="string",
required parameter 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",
required parameter 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},
required parameter name="table-name",
orderBy={{
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
}, {...}},
singlePass=TRUE | FALSE,
vars={{
format="string",
formattedLength=integer,
label="string",
required parameter 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 | informix-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sapiq-parameters | sforce-parameters | singlestore_standard-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | ss_noreq-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}
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}
required parameter name="table-name"
vars={{
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
}, {...}}
where="where-expression"
}
},
target="string",
weight="variable-name"
;
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.
Parameters for Creating Output Tables

Parameter

Subparameter

Description

required parameteroutput

required parametercasOut

creates a table on the server that contains the design matrix of a specified model.

 outputTables

names

lists the names of results tables to save as CAS tables on the server.

Parameter Descriptions

attributes={{casinvardesc-1} <, {casinvardesc-2}, ...>}

changes the attributes of variables used in this action. Currently, attributes specified on the inputs and nominals parameter are ignored.

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

Alias attribute

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

names the classification variables to be used as explanatory variables in the analysis.

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

Alias classVars

collection={{collection-1} <, {collection-2}, ...>}

defines a set of variables that are treated as a single effect that has multiple degrees of freedom.

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

details=TRUE | FALSE

when set to True, requests a table that shows additional details that are related to this effect.

Default FALSE
* name="string"

specifies the name of the effect.

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

specifies a set of variables that are treated as a single effect that has multiple degrees of freedom. The columns in the design matrix that are contributed by a collection effect are the design columns of its constituent variables in the order in which they appear in the definition of the collection effect.

display={displayTables}

specifies a list of results tables to send to the client for display.

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

freq="variable-name"

names the numeric variable that contains the frequency of occurrence of each observation.

inputs={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies variables to use for analysis.

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

Alias input

model={outdesModelList}

names the dependent variable, explanatory effects, and model options.

The outdesModelList 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
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.

entry="variable-name"

specifies the entry variable.

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

defines an effect that specifies heterogeneity in the covariance structure of G for mixed models. All observations that have the same level of the group effect have the same covariance parameters. Each new level of the group effect produces a new set of covariance parameters that has the same structure as the original group.

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.

include=integer | {{effect-1} <, {effect-2}, ...>}

specifies effects to include at the start of the selection process for the specified selection method. Included effects are never dropped during the selection process. If you specify n, where n is a positive integer, then the included effects consist of the first n effects of the model specification.

The effect value is specified as follows:

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.

informative=TRUE | FALSE

when set to True, models missing values by using extra model effects. These effects consist of dummy variables that take the value 1 when the value of a continuous model variable involved in the effect is missing, and take the value 0 otherwise. The missing value in the original model effect is replaced by the average value of the effect for the nonmissing values. For classification variables, missing values are treated as valid levels.

Default FALSE
noint=TRUE | FALSE

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

Default FALSE
start=integer | {{effect-1} <, {effect-2}, ...>}

specifies effects to use to begin the selection process in the FORWARD, FORWARDSWAP, and STEPWISE selection methods. If you specify n, where n is a positive integer, then the starting model consists of the first n effects of the model specification.

The effect value is specified as follows:

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.

multimember={{multimember-1} <, {multimember-2}, ...>}

uses one or more classification variables specified in the vars parameter in such a way that each observation can be associated with one or more levels of the union of the levels of the classification variables.

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

nominals={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies nominal variables to use for analysis.

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

Alias nominal

* output={outDesignOutputStatement}

creates a table on the server that contains the design matrix of a specified model.

Alias outDesign

The outDesignOutputStatement 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 (Form 1) 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.

prefix="string"

replaces the column names of the design matrix with the user-specified prefix, followed by the column index.

Aliases pref
prf
Default "Col"

outputTables={outputTables}

lists the names of results tables to save as CAS tables on the server.

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

Alias displayOut

polynomial={{polynomial-1} <, {polynomial-2}, ...>}

specifies a polynomial effect. All specified variables must be numeric. A design matrix column is generated for each term of the specified polynomial. By default, each of these terms is treated as a separate effect for the purpose of model building.

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

Alias poly

spline={{spline-1} <, {spline-2}, ...>}

expands variables into spline bases whose form depends on the specified parameters.

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

* table={castable}

specifies the input data table.

For more information about specifying the table parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).

target="string"

specifies the target variable to use for analysis.

weight="variable-name"

names the numeric variable to use to perform a weighted analysis of the data.

modelMatrix Action

creates a table on the server that contains the design matrix associated with a given model statement..

Lua Syntax

results, info = s:regression_modelMatrix{
attributes={{
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
}, {...}},
class={{
countMissing=true | false,
descending=true | false,
ignoreMissing=true | false,
levelizeRaw=true | false,
maxLev=integer,
order="FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL",
param="BTH" | "EFFECT" | "GLM" | "ORDINAL" | "ORTHBTH" | "ORTHEFFECT" | "ORTHORDINAL" | "ORTHPOLY" | "ORTHREF" | "POLYNOMIAL" | "REFERENCE",
ref="FIRST" | "LAST" | double | "string",
split=true | false,
required parameter vars={"variable-name-1" <, "variable-name-2", ...>}
}, {...}},
collection={{
details=true | false,
required parameter name="string",
required parameter 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
},
freq="variable-name",
inputs={{
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
}, {...}},
model={
depVars={{
name="variable-name"
}, {...}},
effects={{
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest={"string-1" <, "string-2", ...>},
required parameter vars={"string-1" <, "string-2", ...>}
}, {...}},
entry="variable-name",
group={{
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest={"string-1" <, "string-2", ...>},
required parameter vars={"string-1" <, "string-2", ...>}
}, {...}},
include=integer | {{effect-1} <, {effect-2}, ...>},
informative=true | false,
noint=true | false,
start=integer | {{effect-1} <, {effect-2}, ...>}
},
multimember={{
details=true | false,
required parameter name="string",
noEffect=true | false,
stdize=true | false,
required parameter vars={"variable-name-1" <, "variable-name-2", ...>},
weight={"variable-name-1" <, "variable-name-2", ...>}
}, {...}},
nominals={{
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
}, {...}},
required parameter output={
required parameter 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"
promote=true | false
replace=true | false
replication=integer
tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE"
threadBlockSize=64-bit-integer
timeStamp="string"
where={"string-1" <, "string-2", ...>}
},
copyVars="ALL" | "ALL_MODEL" | "ALL_NUMERIC" | {"variable-name-1" <, "variable-name-2", ...>},
prefix="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
},
polynomial={{
degree=integer,
details=true | false,
labelStyle={
expand=true | false
exponent="string"
includeName=true | false
productSymbol="NONE" | "string"
},
mDegree=integer,
required parameter name="string",
noSeparate=true | false,
standardize={
method="MOMENTS" | "MRANGE" | "WMOMENTS"
options="CENTER" | "CENTERSCALE" | "NONE" | "SCALE"
prefix="NONE" | "string"
},
required parameter vars={"variable-name-1" <, "variable-name-2", ...>}
}, {...}},
spline={{
basis="BSPLINE" | "TPF_DEFAULT" | "TPF_NOINT" | "TPF_NOINTANDNOPOWERS" | "TPF_NOPOWERS",
dataBoundary=true | false,
degree=integer,
details=true | false,
knotMax=double,
knotMethod={
equal=integer
list={double-1 <, double-2, ...>}
listWithBoundary={double-1 <, double-2, ...>}
multiscale={
endScale=integer
startScale=integer
}
rangeFractions={double-1 <, double-2, ...>}
},
knotMin=double,
required parameter name="string",
naturalCubic=true | false,
separate=true | false,
split=true | false,
required parameter vars={"variable-name-1" <, "variable-name-2", ...>}
}, {...}},
required parameter table={
caslib="string",
computedOnDemand=true | false,
computedVars={{
format="string",
formattedLength=integer,
label="string",
required parameter 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",
required parameter 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},
required parameter name="table-name",
orderBy={{
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
}, {...}},
singlePass=true | false,
vars={{
format="string",
formattedLength=integer,
label="string",
required parameter 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 | informix-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sapiq-parameters | sforce-parameters | singlestore_standard-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | ss_noreq-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}
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}
required parameter name="table-name"
vars={{
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
}, {...}}
where="where-expression"
}
},
target="string",
weight="variable-name"
}
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.
Parameters for Creating Output Tables

Parameter

Subparameter

Description

required parameteroutput

required parametercasOut

creates a table on the server that contains the design matrix of a specified model.

 outputTables

names

lists the names of results tables to save as CAS tables on the server.

Parameter Descriptions

attributes={{casinvardesc-1} <, {casinvardesc-2}, ...>}

changes the attributes of variables used in this action. Currently, attributes specified on the inputs and nominals parameter are ignored.

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

Alias attribute

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

names the classification variables to be used as explanatory variables in the analysis.

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

Alias classVars

collection={{collection-1} <, {collection-2}, ...>}

defines a set of variables that are treated as a single effect that has multiple degrees of freedom.

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

details=true | false

when set to True, requests a table that shows additional details that are related to this effect.

Default false
* name="string"

specifies the name of the effect.

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

specifies a set of variables that are treated as a single effect that has multiple degrees of freedom. The columns in the design matrix that are contributed by a collection effect are the design columns of its constituent variables in the order in which they appear in the definition of the collection effect.

display={displayTables}

specifies a list of results tables to send to the client for display.

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

freq="variable-name"

names the numeric variable that contains the frequency of occurrence of each observation.

inputs={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies variables to use for analysis.

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

Alias input

model={outdesModelList}

names the dependent variable, explanatory effects, and model options.

The outdesModelList 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
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.

entry="variable-name"

specifies the entry variable.

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

defines an effect that specifies heterogeneity in the covariance structure of G for mixed models. All observations that have the same level of the group effect have the same covariance parameters. Each new level of the group effect produces a new set of covariance parameters that has the same structure as the original group.

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.

include=integer | {{effect-1} <, {effect-2}, ...>}

specifies effects to include at the start of the selection process for the specified selection method. Included effects are never dropped during the selection process. If you specify n, where n is a positive integer, then the included effects consist of the first n effects of the model specification.

The effect value is specified as follows:

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.

informative=true | false

when set to True, models missing values by using extra model effects. These effects consist of dummy variables that take the value 1 when the value of a continuous model variable involved in the effect is missing, and take the value 0 otherwise. The missing value in the original model effect is replaced by the average value of the effect for the nonmissing values. For classification variables, missing values are treated as valid levels.

Default false
noint=true | false

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

Default false
start=integer | {{effect-1} <, {effect-2}, ...>}

specifies effects to use to begin the selection process in the FORWARD, FORWARDSWAP, and STEPWISE selection methods. If you specify n, where n is a positive integer, then the starting model consists of the first n effects of the model specification.

The effect value is specified as follows:

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.

multimember={{multimember-1} <, {multimember-2}, ...>}

uses one or more classification variables specified in the vars parameter in such a way that each observation can be associated with one or more levels of the union of the levels of the classification variables.

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

nominals={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies nominal variables to use for analysis.

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

Alias nominal

* output={outDesignOutputStatement}

creates a table on the server that contains the design matrix of a specified model.

Alias outDesign

The outDesignOutputStatement 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 (Form 1) 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.

prefix="string"

replaces the column names of the design matrix with the user-specified prefix, followed by the column index.

Aliases pref
prf
Default "Col"

outputTables={outputTables}

lists the names of results tables to save as CAS tables on the server.

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

Alias displayOut

polynomial={{polynomial-1} <, {polynomial-2}, ...>}

specifies a polynomial effect. All specified variables must be numeric. A design matrix column is generated for each term of the specified polynomial. By default, each of these terms is treated as a separate effect for the purpose of model building.

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

Alias poly

spline={{spline-1} <, {spline-2}, ...>}

expands variables into spline bases whose form depends on the specified parameters.

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

* table={castable}

specifies the input data table.

For more information about specifying the table parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).

target="string"

specifies the target variable to use for analysis.

weight="variable-name"

names the numeric variable to use to perform a weighted analysis of the data.

modelMatrix Action

creates a table on the server that contains the design matrix associated with a given model statement..

Python Syntax

results=s.regression.modelMatrix(
attributes=[{
"format":"string",
"formattedLength":integer,
"label":"string",
required parameter "name":"variable-name",
"nfd":integer,
"nfl":integer
}<, {...}>],
class_=[{
"countMissing":True | False,
"descending":True | False,
"ignoreMissing":True | False,
"levelizeRaw":True | False,
"maxLev":integer,
"order":"FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL",
"param":"BTH" | "EFFECT" | "GLM" | "ORDINAL" | "ORTHBTH" | "ORTHEFFECT" | "ORTHORDINAL" | "ORTHPOLY" | "ORTHREF" | "POLYNOMIAL" | "REFERENCE",
"ref":"FIRST" | "LAST" | double | "string",
"split":True | False,
required parameter "vars":["variable-name-1" <, "variable-name-2", ...>]
}<, {...}>],
collection=[{
"details":True | False,
required parameter "name":"string",
required parameter "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
},
freq="variable-name",
inputs=[{
"format":"string",
"formattedLength":integer,
"label":"string",
required parameter "name":"variable-name",
"nfd":integer,
"nfl":integer
}<, {...}>],
model={
"depVars":[{
"name":"variable-name"
}<, {...}>],
"effects":[{
"interaction":"BAR" | "CROSS" | "NONE",
"maxInteract":integer,
"nest":["string-1" <, "string-2", ...>],
required parameter "vars":["string-1" <, "string-2", ...>]
}<, {...}>],
"entry":"variable-name",
"group":[{
"interaction":"BAR" | "CROSS" | "NONE",
"maxInteract":integer,
"nest":["string-1" <, "string-2", ...>],
required parameter "vars":["string-1" <, "string-2", ...>]
}<, {...}>],
"include":integer | [{effect-1} <, {effect-2}, ...>],
"informative":True | False,
"noint":True | False,
"start":integer | [{effect-1} <, {effect-2}, ...>]
},
multimember=[{
"details":True | False,
required parameter "name":"string",
"noEffect":True | False,
"stdize":True | False,
required parameter "vars":["variable-name-1" <, "variable-name-2", ...>],
"weight":["variable-name-1" <, "variable-name-2", ...>]
}<, {...}>],
nominals=[{
"format":"string",
"formattedLength":integer,
"label":"string",
required parameter "name":"variable-name",
"nfd":integer,
"nfl":integer
}<, {...}>],
required parameter output={
required parameter "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"
"promote":True | False
"replace":True | False
"replication":integer
"tableRedistUpPolicy":"DEFER" | "NOREDIST" | "REBALANCE"
"threadBlockSize":64-bit-integer
"timeStamp":"string"
"where":["string-1" <, "string-2", ...>]
},
"copyVars":"ALL" | "ALL_MODEL" | "ALL_NUMERIC" | ["variable-name-1" <, "variable-name-2", ...>],
"prefix":"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
},
polynomial=[{
"degree":integer,
"details":True | False,
"labelStyle":{
"expand":True | False
"exponent":"string"
"includeName":True | False
"productSymbol":"NONE" | "string"
},
"mDegree":integer,
required parameter "name":"string",
"noSeparate":True | False,
"standardize":{
"method":"MOMENTS" | "MRANGE" | "WMOMENTS"
"options":"CENTER" | "CENTERSCALE" | "NONE" | "SCALE"
"prefix":"NONE" | "string"
},
required parameter "vars":["variable-name-1" <, "variable-name-2", ...>]
}<, {...}>],
spline=[{
"basis":"BSPLINE" | "TPF_DEFAULT" | "TPF_NOINT" | "TPF_NOINTANDNOPOWERS" | "TPF_NOPOWERS",
"dataBoundary":True | False,
"degree":integer,
"details":True | False,
"knotMax":double,
"knotMethod":{
"equal":integer
"list":[double-1 <, double-2, ...>]
"listWithBoundary":[double-1 <, double-2, ...>]
"multiscale":{
"endScale":integer
"startScale":integer
}
"rangeFractions":[double-1 <, double-2, ...>]
},
"knotMin":double,
required parameter "name":"string",
"naturalCubic":True | False,
"separate":True | False,
"split":True | False,
required parameter "vars":["variable-name-1" <, "variable-name-2", ...>]
}<, {...}>],
required parameter table={
"caslib":"string",
"computedOnDemand":True | False,
"computedVars":[{
"format":"string",
"formattedLength":integer,
"label":"string",
required parameter "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",
required parameter "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},
required parameter "name":"table-name",
"orderBy":[{
"format":"string",
"formattedLength":integer,
"label":"string",
required parameter "name":"variable-name",
"nfd":integer,
"nfl":integer
}<, {...}>],
"singlePass":True | False,
"vars":[{
"format":"string",
"formattedLength":integer,
"label":"string",
required parameter "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 | informix-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sapiq-parameters | sforce-parameters | singlestore_standard-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | ss_noreq-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}
"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}
required parameter "name":"table-name"
"vars":[{
"format":"string",
"formattedLength":integer,
"label":"string",
required parameter "name":"variable-name",
"nfd":integer,
"nfl":integer
}<, {...}>]
"where":"where-expression"
}
},
target="string",
weight="variable-name"
)
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.
Parameters for Creating Output Tables

Parameter

Subparameter

Description

required parameteroutput

required parametercasOut

creates a table on the server that contains the design matrix of a specified model.

 outputTables

names

lists the names of results tables to save as CAS tables on the server.

Parameter Descriptions

attributes=[{casinvardesc-1} <, {casinvardesc-2}, ...>]

changes the attributes of variables used in this action. Currently, attributes specified on the inputs and nominals parameter are ignored.

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

Alias attribute

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

names the classification variables to be used as explanatory variables in the analysis.

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

Alias classVars

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

defines a set of variables that are treated as a single effect that has multiple degrees of freedom.

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

"details":True | False

when set to True, requests a table that shows additional details that are related to this effect.

Default False
* "name":"string"

specifies the name of the effect.

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

specifies a set of variables that are treated as a single effect that has multiple degrees of freedom. The columns in the design matrix that are contributed by a collection effect are the design columns of its constituent variables in the order in which they appear in the definition of the collection effect.

display={displayTables}

specifies a list of results tables to send to the client for display.

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

freq="variable-name"

names the numeric variable that contains the frequency of occurrence of each observation.

inputs=[{casinvardesc-1} <, {casinvardesc-2}, ...>]

specifies variables to use for analysis.

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

Alias input

model={outdesModelList}

names the dependent variable, explanatory effects, and model options.

The outdesModelList 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
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.

"entry":"variable-name"

specifies the entry variable.

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

defines an effect that specifies heterogeneity in the covariance structure of G for mixed models. All observations that have the same level of the group effect have the same covariance parameters. Each new level of the group effect produces a new set of covariance parameters that has the same structure as the original group.

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.

"include":integer | [{effect-1} <, {effect-2}, ...>]

specifies effects to include at the start of the selection process for the specified selection method. Included effects are never dropped during the selection process. If you specify n, where n is a positive integer, then the included effects consist of the first n effects of the model specification.

The effect value is specified as follows:

"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.

"informative":True | False

when set to True, models missing values by using extra model effects. These effects consist of dummy variables that take the value 1 when the value of a continuous model variable involved in the effect is missing, and take the value 0 otherwise. The missing value in the original model effect is replaced by the average value of the effect for the nonmissing values. For classification variables, missing values are treated as valid levels.

Default False
"noint":True | False

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

Default False
"start":integer | [{effect-1} <, {effect-2}, ...>]

specifies effects to use to begin the selection process in the FORWARD, FORWARDSWAP, and STEPWISE selection methods. If you specify n, where n is a positive integer, then the starting model consists of the first n effects of the model specification.

The effect value is specified as follows:

"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.

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

uses one or more classification variables specified in the vars parameter in such a way that each observation can be associated with one or more levels of the union of the levels of the classification variables.

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

nominals=[{casinvardesc-1} <, {casinvardesc-2}, ...>]

specifies nominal variables to use for analysis.

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

Alias nominal

* output={outDesignOutputStatement}

creates a table on the server that contains the design matrix of a specified model.

Alias outDesign

The outDesignOutputStatement 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 (Form 1) 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.

"prefix":"string"

replaces the column names of the design matrix with the user-specified prefix, followed by the column index.

Aliases pref
prf
Default "Col"

outputTables={outputTables}

lists the names of results tables to save as CAS tables on the server.

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

Alias displayOut

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

specifies a polynomial effect. All specified variables must be numeric. A design matrix column is generated for each term of the specified polynomial. By default, each of these terms is treated as a separate effect for the purpose of model building.

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

Alias poly

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

expands variables into spline bases whose form depends on the specified parameters.

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

* table={castable}

specifies the input data table.

For more information about specifying the table parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).

target="string"

specifies the target variable to use for analysis.

weight="variable-name"

names the numeric variable to use to perform a weighted analysis of the data.

modelMatrix Action

creates a table on the server that contains the design matrix associated with a given model statement..

R Syntax

results <– cas.regression.modelMatrix(s,
attributes=list( list(
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
) <, list(...)>),
class=list( list(
countMissing=TRUE | FALSE,
descending=TRUE | FALSE,
ignoreMissing=TRUE | FALSE,
levelizeRaw=TRUE | FALSE,
maxLev=integer,
order="FORMATTED" | "FREQ" | "FREQFORMATTED" | "FREQINTERNAL" | "INTERNAL",
param="BTH" | "EFFECT" | "GLM" | "ORDINAL" | "ORTHBTH" | "ORTHEFFECT" | "ORTHORDINAL" | "ORTHPOLY" | "ORTHREF" | "POLYNOMIAL" | "REFERENCE",
ref="FIRST" | "LAST" | double | "string",
split=TRUE | FALSE,
required parameter vars=list("variable-name-1" <, "variable-name-2", ...>)
) <, list(...)>),
collection=list( list(
details=TRUE | FALSE,
required parameter name="string",
required parameter 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
),
freq="variable-name",
inputs=list( list(
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
) <, list(...)>),
model=list(
depVars=list( list(
name="variable-name"
) <, list(...)>),
effects=list( list(
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest=list("string-1" <, "string-2", ...>),
required parameter vars=list("string-1" <, "string-2", ...>)
) <, list(...)>),
entry="variable-name",
group=list( list(
interaction="BAR" | "CROSS" | "NONE",
maxInteract=integer,
nest=list("string-1" <, "string-2", ...>),
required parameter vars=list("string-1" <, "string-2", ...>)
) <, list(...)>),
include=integer | list( list(effect-1) <, list(effect-2), ...>),
informative=TRUE | FALSE,
noint=TRUE | FALSE,
start=integer | list( list(effect-1) <, list(effect-2), ...>)
),
multimember=list( list(
details=TRUE | FALSE,
required parameter name="string",
noEffect=TRUE | FALSE,
stdize=TRUE | FALSE,
required parameter vars=list("variable-name-1" <, "variable-name-2", ...>),
weight=list("variable-name-1" <, "variable-name-2", ...>)
) <, list(...)>),
nominals=list( list(
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
) <, list(...)>),
required parameter output=list(
required parameter 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"
promote=TRUE | FALSE
replace=TRUE | FALSE
replication=integer
tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE"
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", ...>),
prefix="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
),
polynomial=list( list(
degree=integer,
details=TRUE | FALSE,
labelStyle=list(
expand=TRUE | FALSE
exponent="string"
includeName=TRUE | FALSE
productSymbol="NONE" | "string"
),
mDegree=integer,
required parameter name="string",
noSeparate=TRUE | FALSE,
standardize=list(
method="MOMENTS" | "MRANGE" | "WMOMENTS"
options="CENTER" | "CENTERSCALE" | "NONE" | "SCALE"
prefix="NONE" | "string"
),
required parameter vars=list("variable-name-1" <, "variable-name-2", ...>)
) <, list(...)>),
spline=list( list(
basis="BSPLINE" | "TPF_DEFAULT" | "TPF_NOINT" | "TPF_NOINTANDNOPOWERS" | "TPF_NOPOWERS",
dataBoundary=TRUE | FALSE,
degree=integer,
details=TRUE | FALSE,
knotMax=double,
knotMethod=list(
equal=integer
list=list(double-1 <, double-2, ...>)
listWithBoundary=list(double-1 <, double-2, ...>)
multiscale=list(
endScale=integer
startScale=integer
)
rangeFractions=list(double-1 <, double-2, ...>)
),
knotMin=double,
required parameter name="string",
naturalCubic=TRUE | FALSE,
separate=TRUE | FALSE,
split=TRUE | FALSE,
required parameter vars=list("variable-name-1" <, "variable-name-2", ...>)
) <, list(...)>),
required parameter table=list(
caslib="string",
computedOnDemand=TRUE | FALSE,
computedVars=list( list(
format="string",
formattedLength=integer,
label="string",
required parameter 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",
required parameter name="variable-name",
nfd=integer,
nfl=integer
) <, list(...)>),
groupByMode="NOSORT" | "REDISTRIBUTE",
importOptions=list(fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DELIMITED" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SOUND" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters),
required parameter name="table-name",
orderBy=list( list(
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
) <, list(...)>),
singlePass=TRUE | FALSE,
vars=list( list(
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
) <, list(...)>),
where="where-expression",
whereTable=list(
casLib="string"
dataSourceOptions=list(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 | informix-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sapiq-parameters | sforce-parameters | singlestore_standard-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | ss_noreq-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters)
importOptions=list(fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DELIMITED" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SOUND" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters)
required parameter name="table-name"
vars=list( list(
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
) <, list(...)>)
where="where-expression"
)
),
target="string",
weight="variable-name"
)
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.
Parameters for Creating Output Tables

Parameter

Subparameter

Description

required parameteroutput

required parametercasOut

creates a table on the server that contains the design matrix of a specified model.

 outputTables

names

lists the names of results tables to save as CAS tables on the server.

Parameter Descriptions

attributes=list( list(casinvardesc-1) <, list(casinvardesc-2), ...>)

changes the attributes of variables used in this action. Currently, attributes specified on the inputs and nominals parameter are ignored.

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

Alias attribute

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

names the classification variables to be used as explanatory variables in the analysis.

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

Alias classVars

collection=list( list(collection-1) <, list(collection-2), ...>)

defines a set of variables that are treated as a single effect that has multiple degrees of freedom.

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

details=TRUE | FALSE

when set to True, requests a table that shows additional details that are related to this effect.

Default FALSE
* name="string"

specifies the name of the effect.

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

specifies a set of variables that are treated as a single effect that has multiple degrees of freedom. The columns in the design matrix that are contributed by a collection effect are the design columns of its constituent variables in the order in which they appear in the definition of the collection effect.

display=list(displayTables)

specifies a list of results tables to send to the client for display.

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

freq="variable-name"

names the numeric variable that contains the frequency of occurrence of each observation.

inputs=list( list(casinvardesc-1) <, list(casinvardesc-2), ...>)

specifies variables to use for analysis.

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

Alias input

model=list(outdesModelList)

names the dependent variable, explanatory effects, and model options.

The outdesModelList 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
target
name="variable-name"

names the response variable.

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

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

entry="variable-name"

specifies the entry variable.

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

defines an effect that specifies heterogeneity in the covariance structure of G for mixed models. All observations that have the same level of the group effect have the same covariance parameters. Each new level of the group effect produces a new set of covariance parameters that has the same structure as the original group.

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", ...>)

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

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

include=integer | list( list(effect-1) <, list(effect-2), ...>)

specifies effects to include at the start of the selection process for the specified selection method. Included effects are never dropped during the selection process. If you specify n, where n is a positive integer, then the included effects consist of the first n effects of the model specification.

The effect value is specified as follows:

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", ...>)

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

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

informative=TRUE | FALSE

when set to True, models missing values by using extra model effects. These effects consist of dummy variables that take the value 1 when the value of a continuous model variable involved in the effect is missing, and take the value 0 otherwise. The missing value in the original model effect is replaced by the average value of the effect for the nonmissing values. For classification variables, missing values are treated as valid levels.

Default FALSE
noint=TRUE | FALSE

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

Default FALSE
start=integer | list( list(effect-1) <, list(effect-2), ...>)

specifies effects to use to begin the selection process in the FORWARD, FORWARDSWAP, and STEPWISE selection methods. If you specify n, where n is a positive integer, then the starting model consists of the first n effects of the model specification.

The effect value is specified as follows:

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", ...>)

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

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

multimember=list( list(multimember-1) <, list(multimember-2), ...>)

uses one or more classification variables specified in the vars parameter in such a way that each observation can be associated with one or more levels of the union of the levels of the classification variables.

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

nominals=list( list(casinvardesc-1) <, list(casinvardesc-2), ...>)

specifies nominal variables to use for analysis.

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

Alias nominal

* output=list(outDesignOutputStatement)

creates a table on the server that contains the design matrix of a specified model.

Alias outDesign

The outDesignOutputStatement 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 (Form 1) parameter (Appendix A: Common Parameters).

copyVars="ALL" | "ALL_MODEL" | "ALL_NUMERIC" | list("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.

prefix="string"

replaces the column names of the design matrix with the user-specified prefix, followed by the column index.

Aliases pref
prf
Default "Col"

outputTables=list(outputTables)

lists the names of results tables to save as CAS tables on the server.

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

Alias displayOut

polynomial=list( list(polynomial-1) <, list(polynomial-2), ...>)

specifies a polynomial effect. All specified variables must be numeric. A design matrix column is generated for each term of the specified polynomial. By default, each of these terms is treated as a separate effect for the purpose of model building.

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

Alias poly

spline=list( list(spline-1) <, list(spline-2), ...>)

expands variables into spline bases whose form depends on the specified parameters.

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

* table=list(castable)

specifies the input data table.

For more information about specifying the table parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).

target="string"

specifies the target variable to use for analysis.

weight="variable-name"

names the numeric variable to use to perform a weighted analysis of the data.

Last updated: March 05, 2026