Factor Analysis Action Set

Actions used in the Cloud Analytic Services for performing factor analysis

faNFactors Action

Determines the number of factors.

CASL Syntax

factorAnalysis.faNFactors <result=results> <status=rc> /
attributes={{
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
}, {...}},
corrOut={
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,
tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE",
threadBlockSize=64-bit-integer,
timeStamp="string",
where={"string-1" <, "string-2", ...>}
},
required parameter criteria={{
alpha={double-1 <, double-2, ...>},
nSimulations={64-bit-integer-1 <, 64-bit-integer-2, ...>},
seed={64-bit-integer-1 <, 64-bit-integer-2, ...>},
status="ACTIVE" | "INACTIVE",
threshold={double-1 <, double-2, ...>},
required parameter type="EIGENVALUE" | "MAP2" | "MAP4" | "PARALLEL" | "PROPORTION"
}, {...}},
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
}, {...}},
nFactors="MAX" | "MEAN" | "MEDIAN" | "MIN",
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
},
priors={type="ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters},
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",
onDemand=TRUE | FALSE,
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"
}
},
varianceDivisor="DF" | "N" | "WDF" | "WEIGHT",
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

 table

—

specifies the settings for an input table.
Parameters for Creating Output Tables

Parameter

Subparameter

Description

 corrOut

—

specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.

 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).

Aliases attribute
attr

corrOut={casouttable}

specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.

For more information about specifying the corrOut parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).

* criteria={{faNFactors_criterion-1} <, {faNFactors_criterion-2}, ...>}

specifies one or more criteria to determine the number of factors.

Alias criterion

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

alpha={double-1 <, double-2, ...>}

specifies the critical value for the parallel analysis. For the parallel analysis criterion, if you do not specify the critical value, a default value of 0.05 is used. For all other criteria, the critical value is ignored.

Requirement The specified values must be unique.
nSimulations={64-bit-integer-1 <, 64-bit-integer-2, ...>}

specifies the number of simulations to use in the parallel analysis. For the parallel analysis criterion, if you do not specify the number of simulations, a default value of 10,000 is used. For all other criteria, the number of simulations is ignored.

Aliases nSims
nSim
Requirement The specified values must be unique.
seed={64-bit-integer-1 <, 64-bit-integer-2, ...>}

specifies the pseudorandom number seed for the parallel analysis.

Requirement The specified values must be unique.
status="ACTIVE" | "INACTIVE"

specifies the status of the factor determination criterion.

Default ACTIVE
ACTIVE

uses the criterion to determine the number of factors.

INACTIVE

specifies that the criterion is for informational purposes only.

threshold={double-1 <, double-2, ...>}

specifies one or more threshold values. The threshold values are used by the eigenvalue criterion and the proportion of variance criterion only. For these criteria, if you do not specify a threshold value, a default value of 1.0 is used. For all other criteria, the threshold value is ignored.

Requirement The specified values must be unique.
* type="EIGENVALUE" | "MAP2" | "MAP4" | "PARALLEL" | "PROPORTION"

specifies the criterion type for determining the number of factors.

EIGENVALUE

specifies the minimum eigenvalue criterion.

MAP2

specifies the minimum average squared partial correlation criterion.

Alias MAP
MAP4

specifies the minimum average fourth-power partial correlation criterion.

PARALLEL

specifies a parallel analysis.

PROPORTION

specifies the proportion of variance explained criterion.

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"

specifies a 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).

Aliases input
vars
var

nFactors="MAX" | "MEAN" | "MEDIAN" | "MIN"

specifies how to determine the final number of factors.

Default MIN
MAX

specifies that the number of factors is the maximum of all active criteria.

MEAN

specifies that the number of factors is the mean (rounded) of all active criteria.

MEDIAN

specifies that the number of factors is the median (rounded) of all active criteria.

MIN

specifies that the number of factors is the minimum of all active criteria.

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

priors={type="ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters}

specifies the method of computing prior communality estimates.

The value that you specify for the type parameter determines the other parameters that apply.

Default SMC

table={castable}

specifies the settings for an input table.

For more information about specifying the table parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).

varianceDivisor="DF" | "N" | "WDF" | "WEIGHT"

specifies the variance divisor for calculating variances and covariances.

Alias varDef
Default DF
DF

divides by the degrees of freedom.

N

divides by the number of observations.

WDF

divides by the sum of weights minus one.

WEIGHT

divides by the sum of weights.

weight="variable-name"

specifies a numeric variable to use as a weight to perform a weighted analysis of the data.

Parameters for type="ASMC"

No parameters apply when you specify ASMC.

Parameters for type="INPUT"

* values={double-1 <, double-2, ...>}

specifies the values to use for the prior communality estimates.

Parameters for type="MAX"

No parameters apply when you specify MAX.

Parameters for type="ONE"

No parameters apply when you specify ONE.

Parameters for type="RANDOM"

seed=64-bit-integer

specifies the seed for the pseudorandom number generator that is used to assign prior communality estimates.

Default 0

Parameters for type="SMC"

No parameters apply when you specify SMC.

faNFactors Action

Determines the number of factors.

Lua Syntax

results, info = s:factorAnalysis_faNFactors{
attributes={{
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
}, {...}},
corrOut={
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,
tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE",
threadBlockSize=64-bit-integer,
timeStamp="string",
where={"string-1" <, "string-2", ...>}
},
required parameter criteria={{
alpha={double-1 <, double-2, ...>},
nSimulations={64-bit-integer-1 <, 64-bit-integer-2, ...>},
seed={64-bit-integer-1 <, 64-bit-integer-2, ...>},
status="ACTIVE" | "INACTIVE",
threshold={double-1 <, double-2, ...>},
required parameter type="EIGENVALUE" | "MAP2" | "MAP4" | "PARALLEL" | "PROPORTION"
}, {...}},
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
}, {...}},
nFactors="MAX" | "MEAN" | "MEDIAN" | "MIN",
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
},
priors={type="ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters},
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",
onDemand=true | false,
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"
}
},
varianceDivisor="DF" | "N" | "WDF" | "WEIGHT",
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

 table

—

specifies the settings for an input table.
Parameters for Creating Output Tables

Parameter

Subparameter

Description

 corrOut

—

specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.

 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).

Aliases attribute
attr

corrOut={casouttable}

specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.

For more information about specifying the corrOut parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).

* criteria={{faNFactors_criterion-1} <, {faNFactors_criterion-2}, ...>}

specifies one or more criteria to determine the number of factors.

Alias criterion

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

alpha={double-1 <, double-2, ...>}

specifies the critical value for the parallel analysis. For the parallel analysis criterion, if you do not specify the critical value, a default value of 0.05 is used. For all other criteria, the critical value is ignored.

Requirement The specified values must be unique.
nSimulations={64-bit-integer-1 <, 64-bit-integer-2, ...>}

specifies the number of simulations to use in the parallel analysis. For the parallel analysis criterion, if you do not specify the number of simulations, a default value of 10,000 is used. For all other criteria, the number of simulations is ignored.

Aliases nSims
nSim
Requirement The specified values must be unique.
seed={64-bit-integer-1 <, 64-bit-integer-2, ...>}

specifies the pseudorandom number seed for the parallel analysis.

Requirement The specified values must be unique.
status="ACTIVE" | "INACTIVE"

specifies the status of the factor determination criterion.

Default ACTIVE
ACTIVE

uses the criterion to determine the number of factors.

INACTIVE

specifies that the criterion is for informational purposes only.

threshold={double-1 <, double-2, ...>}

specifies one or more threshold values. The threshold values are used by the eigenvalue criterion and the proportion of variance criterion only. For these criteria, if you do not specify a threshold value, a default value of 1.0 is used. For all other criteria, the threshold value is ignored.

Requirement The specified values must be unique.
* type="EIGENVALUE" | "MAP2" | "MAP4" | "PARALLEL" | "PROPORTION"

specifies the criterion type for determining the number of factors.

EIGENVALUE

specifies the minimum eigenvalue criterion.

MAP2

specifies the minimum average squared partial correlation criterion.

Alias MAP
MAP4

specifies the minimum average fourth-power partial correlation criterion.

PARALLEL

specifies a parallel analysis.

PROPORTION

specifies the proportion of variance explained criterion.

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"

specifies a 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).

Aliases input
vars
var

nFactors="MAX" | "MEAN" | "MEDIAN" | "MIN"

specifies how to determine the final number of factors.

Default MIN
MAX

specifies that the number of factors is the maximum of all active criteria.

MEAN

specifies that the number of factors is the mean (rounded) of all active criteria.

MEDIAN

specifies that the number of factors is the median (rounded) of all active criteria.

MIN

specifies that the number of factors is the minimum of all active criteria.

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

priors={type="ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters}

specifies the method of computing prior communality estimates.

The value that you specify for the type parameter determines the other parameters that apply.

Default SMC

table={castable}

specifies the settings for an input table.

For more information about specifying the table parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).

varianceDivisor="DF" | "N" | "WDF" | "WEIGHT"

specifies the variance divisor for calculating variances and covariances.

Alias varDef
Default DF
DF

divides by the degrees of freedom.

N

divides by the number of observations.

WDF

divides by the sum of weights minus one.

WEIGHT

divides by the sum of weights.

weight="variable-name"

specifies a numeric variable to use as a weight to perform a weighted analysis of the data.

Parameters for type="ASMC"

No parameters apply when you specify ASMC.

Parameters for type="INPUT"

* values={double-1 <, double-2, ...>}

specifies the values to use for the prior communality estimates.

Parameters for type="MAX"

No parameters apply when you specify MAX.

Parameters for type="ONE"

No parameters apply when you specify ONE.

Parameters for type="RANDOM"

seed=64-bit-integer

specifies the seed for the pseudorandom number generator that is used to assign prior communality estimates.

Default 0

Parameters for type="SMC"

No parameters apply when you specify SMC.

faNFactors Action

Determines the number of factors.

Python Syntax

results=s.factorAnalysis.faNFactors(
attributes=[{
"format":"string",
"formattedLength":integer,
"label":"string",
required parameter "name":"variable-name",
"nfd":integer,
"nfl":integer
}<, {...}>],
corrOut={
"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,
"tableRedistUpPolicy":"DEFER" | "NOREDIST" | "REBALANCE",
"threadBlockSize":64-bit-integer,
"timeStamp":"string",
"where":["string-1" <, "string-2", ...>]
},
required parameter criteria=[{
"alpha":[double-1 <, double-2, ...>],
"nSimulations":[64-bit-integer-1 <, 64-bit-integer-2, ...>],
"seed":[64-bit-integer-1 <, 64-bit-integer-2, ...>],
"status":"ACTIVE" | "INACTIVE",
"threshold":[double-1 <, double-2, ...>],
required parameter "type":"EIGENVALUE" | "MAP2" | "MAP4" | "PARALLEL" | "PROPORTION"
}<, {...}>],
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
}<, {...}>],
nFactors="MAX" | "MEAN" | "MEDIAN" | "MIN",
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
},
priors={"type":"ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters},
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",
"onDemand":True | False,
"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"
}
},
varianceDivisor="DF" | "N" | "WDF" | "WEIGHT",
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

 table

—

specifies the settings for an input table.
Parameters for Creating Output Tables

Parameter

Subparameter

Description

 corrOut

—

specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.

 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).

Aliases attribute
attr

corrOut={casouttable}

specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.

For more information about specifying the corrOut parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).

* criteria=[{faNFactors_criterion-1} <, {faNFactors_criterion-2}, ...>]

specifies one or more criteria to determine the number of factors.

Alias criterion

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

"alpha":[double-1 <, double-2, ...>]

specifies the critical value for the parallel analysis. For the parallel analysis criterion, if you do not specify the critical value, a default value of 0.05 is used. For all other criteria, the critical value is ignored.

Requirement The specified values must be unique.
"nSimulations":[64-bit-integer-1 <, 64-bit-integer-2, ...>]

specifies the number of simulations to use in the parallel analysis. For the parallel analysis criterion, if you do not specify the number of simulations, a default value of 10,000 is used. For all other criteria, the number of simulations is ignored.

Aliases nSims
nSim
Requirement The specified values must be unique.
"seed":[64-bit-integer-1 <, 64-bit-integer-2, ...>]

specifies the pseudorandom number seed for the parallel analysis.

Requirement The specified values must be unique.
"status":"ACTIVE" | "INACTIVE"

specifies the status of the factor determination criterion.

Default ACTIVE
ACTIVE

uses the criterion to determine the number of factors.

INACTIVE

specifies that the criterion is for informational purposes only.

"threshold":[double-1 <, double-2, ...>]

specifies one or more threshold values. The threshold values are used by the eigenvalue criterion and the proportion of variance criterion only. For these criteria, if you do not specify a threshold value, a default value of 1.0 is used. For all other criteria, the threshold value is ignored.

Requirement The specified values must be unique.
* "type":"EIGENVALUE" | "MAP2" | "MAP4" | "PARALLEL" | "PROPORTION"

specifies the criterion type for determining the number of factors.

EIGENVALUE

specifies the minimum eigenvalue criterion.

MAP2

specifies the minimum average squared partial correlation criterion.

Alias MAP
MAP4

specifies the minimum average fourth-power partial correlation criterion.

PARALLEL

specifies a parallel analysis.

PROPORTION

specifies the proportion of variance explained criterion.

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"

specifies a 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).

Aliases input
vars
var

nFactors="MAX" | "MEAN" | "MEDIAN" | "MIN"

specifies how to determine the final number of factors.

Default MIN
MAX

specifies that the number of factors is the maximum of all active criteria.

MEAN

specifies that the number of factors is the mean (rounded) of all active criteria.

MEDIAN

specifies that the number of factors is the median (rounded) of all active criteria.

MIN

specifies that the number of factors is the minimum of all active criteria.

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

priors={"type":"ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters}

specifies the method of computing prior communality estimates.

The value that you specify for the type parameter determines the other parameters that apply.

Default SMC

table={castable}

specifies the settings for an input table.

For more information about specifying the table parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).

varianceDivisor="DF" | "N" | "WDF" | "WEIGHT"

specifies the variance divisor for calculating variances and covariances.

Alias varDef
Default DF
DF

divides by the degrees of freedom.

N

divides by the number of observations.

WDF

divides by the sum of weights minus one.

WEIGHT

divides by the sum of weights.

weight="variable-name"

specifies a numeric variable to use as a weight to perform a weighted analysis of the data.

Parameters for type="ASMC"

No parameters apply when you specify ASMC.

Parameters for type="INPUT"

* "values":[double-1 <, double-2, ...>]

specifies the values to use for the prior communality estimates.

Parameters for type="MAX"

No parameters apply when you specify MAX.

Parameters for type="ONE"

No parameters apply when you specify ONE.

Parameters for type="RANDOM"

"seed":64-bit-integer

specifies the seed for the pseudorandom number generator that is used to assign prior communality estimates.

Default 0

Parameters for type="SMC"

No parameters apply when you specify SMC.

faNFactors Action

Determines the number of factors.

R Syntax

results <– cas.factorAnalysis.faNFactors(s,
attributes=list( list(
format="string",
formattedLength=integer,
label="string",
required parameter name="variable-name",
nfd=integer,
nfl=integer
) <, list(...)>),
corrOut=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,
tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE",
threadBlockSize=64-bit-integer,
timeStamp="string",
where=list("string-1" <, "string-2", ...>)
),
required parameter criteria=list( list(
alpha=list(double-1 <, double-2, ...>),
nSimulations=list(64-bit-integer-1 <, 64-bit-integer-2, ...>),
seed=list(64-bit-integer-1 <, 64-bit-integer-2, ...>),
status="ACTIVE" | "INACTIVE",
threshold=list(double-1 <, double-2, ...>),
required parameter type="EIGENVALUE" | "MAP2" | "MAP4" | "PARALLEL" | "PROPORTION"
) <, 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(...)>),
nFactors="MAX" | "MEAN" | "MEDIAN" | "MIN",
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
),
priors=list(type="ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters),
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",
onDemand=TRUE | FALSE,
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"
)
),
varianceDivisor="DF" | "N" | "WDF" | "WEIGHT",
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

 table

—

specifies the settings for an input table.
Parameters for Creating Output Tables

Parameter

Subparameter

Description

 corrOut

—

specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.

 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).

Aliases attribute
attr

corrOut=list(casouttable)

specifies an output table to contain the correlation matrix, summary statistics, and number of observations data.

For more information about specifying the corrOut parameter, see the common casouttable (Form 2) parameter (Appendix A: Common Parameters).

* criteria=list( list(faNFactors_criterion-1) <, list(faNFactors_criterion-2), ...>)

specifies one or more criteria to determine the number of factors.

Alias criterion

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

alpha=list(double-1 <, double-2, ...>)

specifies the critical value for the parallel analysis. For the parallel analysis criterion, if you do not specify the critical value, a default value of 0.05 is used. For all other criteria, the critical value is ignored.

Requirement The specified values must be unique.
nSimulations=list(64-bit-integer-1 <, 64-bit-integer-2, ...>)

specifies the number of simulations to use in the parallel analysis. For the parallel analysis criterion, if you do not specify the number of simulations, a default value of 10,000 is used. For all other criteria, the number of simulations is ignored.

Aliases nSims
nSim
Requirement The specified values must be unique.
seed=list(64-bit-integer-1 <, 64-bit-integer-2, ...>)

specifies the pseudorandom number seed for the parallel analysis.

Requirement The specified values must be unique.
status="ACTIVE" | "INACTIVE"

specifies the status of the factor determination criterion.

Default ACTIVE
ACTIVE

uses the criterion to determine the number of factors.

INACTIVE

specifies that the criterion is for informational purposes only.

threshold=list(double-1 <, double-2, ...>)

specifies one or more threshold values. The threshold values are used by the eigenvalue criterion and the proportion of variance criterion only. For these criteria, if you do not specify a threshold value, a default value of 1.0 is used. For all other criteria, the threshold value is ignored.

Requirement The specified values must be unique.
* type="EIGENVALUE" | "MAP2" | "MAP4" | "PARALLEL" | "PROPORTION"

specifies the criterion type for determining the number of factors.

EIGENVALUE

specifies the minimum eigenvalue criterion.

MAP2

specifies the minimum average squared partial correlation criterion.

Alias MAP
MAP4

specifies the minimum average fourth-power partial correlation criterion.

PARALLEL

specifies a parallel analysis.

PROPORTION

specifies the proportion of variance explained criterion.

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"

specifies a 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).

Aliases input
vars
var

nFactors="MAX" | "MEAN" | "MEDIAN" | "MIN"

specifies how to determine the final number of factors.

Default MIN
MAX

specifies that the number of factors is the maximum of all active criteria.

MEAN

specifies that the number of factors is the mean (rounded) of all active criteria.

MEDIAN

specifies that the number of factors is the median (rounded) of all active criteria.

MIN

specifies that the number of factors is the minimum of all active criteria.

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

priors=list(type="ASMC" | "INPUT" | "MAX" | "ONE" | "RANDOM" | "SMC", type-specific-parameters)

specifies the method of computing prior communality estimates.

The value that you specify for the type parameter determines the other parameters that apply.

Default SMC

table=list(castable)

specifies the settings for an input table.

For more information about specifying the table parameter, see the common castable (Form 2) parameter (Appendix A: Common Parameters).

varianceDivisor="DF" | "N" | "WDF" | "WEIGHT"

specifies the variance divisor for calculating variances and covariances.

Alias varDef
Default DF
DF

divides by the degrees of freedom.

N

divides by the number of observations.

WDF

divides by the sum of weights minus one.

WEIGHT

divides by the sum of weights.

weight="variable-name"

specifies a numeric variable to use as a weight to perform a weighted analysis of the data.

Parameters for type="ASMC"

No parameters apply when you specify ASMC.

Parameters for type="INPUT"

* values=list(double-1 <, double-2, ...>)

specifies the values to use for the prior communality estimates.

Parameters for type="MAX"

No parameters apply when you specify MAX.

Parameters for type="ONE"

No parameters apply when you specify ONE.

Parameters for type="RANDOM"

seed=64-bit-integer

specifies the seed for the pseudorandom number generator that is used to assign prior communality estimates.

Default 0

Parameters for type="SMC"

No parameters apply when you specify SMC.

Last updated: March 05, 2026