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Econometrics Programming Guide
 
CASL
Lua
Python
R

Causal Discovery Action Set

Provides actions for causal discovery

dagdiscovery Action

Performs directed acyclic graph (DAG) structure learning.

CASL Syntax

Développer toutRéduire tout
causalDiscovery.dagdiscovery <result=results> <status=rc> /
algorithm="MCV" | "TOP",
alphas={double-1 <, double-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
},
gpu=TRUE | FALSE,
initMethod="DATA" | "RANDOM" | "VARIANCE",
maxIter=64-bit-integer,
out
={
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", ...>}
},
outDag
={
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", ...>}
},
outIterHist
={
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", ...>}
},
outPath
={
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", ...>}
},
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
},
parallel=TRUE | FALSE,
seed=64-bit-integer,
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",
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"
}
},
required parameter vars={"variable-name-1" <, "variable-name-2", ...>}
;
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

 out

—

names the output data table for the initial and final topological orders, and the matrices of parameter estimates, standard deviations, t values, and p-values.

 outDag

—

names the output table for the estimated directed acyclic graph (DAG).

 outIterHist

—

names the output table for the iteration history.

 outPath

—

names the output data table for the parents, children, and paths.

 outputTables

names

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

Parameter Descriptions

algorithm="MCV" | "TOP"

specifies the algorithm to be used for DAG structure learning.

DefaultTOP
MCV

specifies the minimizing conditional variance (MCV) algorithm.

TOP

specifies the topological order permutation (TOP) algorithm.

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

specifies a list of significance levels for selecting the parent sets or edges. If the list contains more than one element, several DAGs are included in the outdag parameter table, one for each alpha value in the parameter list.

Aliasalpha

display={displayTables}

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

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

gpu=TRUE | FALSE

when set to True, uses enabled graphics processing unit (GPU) functions, if possible.

AliasgpuEnabled
DefaultFALSE

initMethod="DATA" | "RANDOM" | "VARIANCE"

specifies the method to use for determining the initial topological order.

DefaultVARIANCE
DATA

specifies that the initial topological order should match the order of variables in the data table.

RANDOM

specifies that the initial topological order should be random.

VARIANCE

specifies that the initial topological order should be based on the variance of variables.

maxIter=64-bit-integer

specifies the maximum number of iterations for searching the space.

Default200
Minimum value0

out={casouttable}

names the output data table for the initial and final topological orders, and the matrices of parameter estimates, standard deviations, t values, and p-values.

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

outDag={casouttable}

names the output table for the estimated directed acyclic graph (DAG).

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

outIterHist={casouttable}

names the output table for the iteration history.

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

AliasoutIter

outPath={casouttable}

names the output data table for the parents, children, and paths.

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

AliasoutP

outputTables={outputTables}

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

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

AliasdisplayOut

parallel=TRUE | FALSE

when set to True, uses multithreading for the algorithm in searching the space.

DefaultTRUE

seed=64-bit-integer

specifies a nonnegative integer to be used as the seed for generating random number sequences.

Default1
Minimum value0

* table={castable}

specifies the input data table.

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

Aliasdata

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

specifies a list of input variables in the input data table.

Aliasinputs

dagdiscovery Action

Performs directed acyclic graph (DAG) structure learning.

Lua Syntax

Développer toutRéduire tout
results, info = s:causalDiscovery_dagdiscovery{
algorithm="MCV" | "TOP",
alphas={double-1 <, double-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
},
gpu=true | false,
initMethod="DATA" | "RANDOM" | "VARIANCE",
maxIter=64-bit-integer,
out
={
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", ...>}
},
outDag
={
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", ...>}
},
outIterHist
={
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", ...>}
},
outPath
={
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", ...>}
},
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
},
parallel=true | false,
seed=64-bit-integer,
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",
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"
}
},
required parameter vars={"variable-name-1" <, "variable-name-2", ...>}
}
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

 out

—

names the output data table for the initial and final topological orders, and the matrices of parameter estimates, standard deviations, t values, and p-values.

 outDag

—

names the output table for the estimated directed acyclic graph (DAG).

 outIterHist

—

names the output table for the iteration history.

 outPath

—

names the output data table for the parents, children, and paths.

 outputTables

names

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

Parameter Descriptions

algorithm="MCV" | "TOP"

specifies the algorithm to be used for DAG structure learning.

DefaultTOP
MCV

specifies the minimizing conditional variance (MCV) algorithm.

TOP

specifies the topological order permutation (TOP) algorithm.

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

specifies a list of significance levels for selecting the parent sets or edges. If the list contains more than one element, several DAGs are included in the outdag parameter table, one for each alpha value in the parameter list.

Aliasalpha

display={displayTables}

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

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

gpu=true | false

when set to True, uses enabled graphics processing unit (GPU) functions, if possible.

AliasgpuEnabled
Defaultfalse

initMethod="DATA" | "RANDOM" | "VARIANCE"

specifies the method to use for determining the initial topological order.

DefaultVARIANCE
DATA

specifies that the initial topological order should match the order of variables in the data table.

RANDOM

specifies that the initial topological order should be random.

VARIANCE

specifies that the initial topological order should be based on the variance of variables.

maxIter=64-bit-integer

specifies the maximum number of iterations for searching the space.

Default200
Minimum value0

out={casouttable}

names the output data table for the initial and final topological orders, and the matrices of parameter estimates, standard deviations, t values, and p-values.

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

outDag={casouttable}

names the output table for the estimated directed acyclic graph (DAG).

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

outIterHist={casouttable}

names the output table for the iteration history.

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

AliasoutIter

outPath={casouttable}

names the output data table for the parents, children, and paths.

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

AliasoutP

outputTables={outputTables}

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

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

AliasdisplayOut

parallel=true | false

when set to True, uses multithreading for the algorithm in searching the space.

Defaulttrue

seed=64-bit-integer

specifies a nonnegative integer to be used as the seed for generating random number sequences.

Default1
Minimum value0

* table={castable}

specifies the input data table.

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

Aliasdata

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

specifies a list of input variables in the input data table.

Aliasinputs

dagdiscovery Action

Performs directed acyclic graph (DAG) structure learning.

Python Syntax

Développer toutRéduire tout
results=s.causalDiscovery.dagdiscovery(
algorithm="MCV" | "TOP",
alphas=[double-1 <, double-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
},
gpu=True | False,
initMethod="DATA" | "RANDOM" | "VARIANCE",
maxIter=64-bit-integer,
out
={
"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", ...>]
},
outDag
={
"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", ...>]
},
outIterHist
={
"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", ...>]
},
outPath
={
"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", ...>]
},
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
},
parallel=True | False,
seed=64-bit-integer,
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",
"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"
}
},
required parameter vars=["variable-name-1" <, "variable-name-2", ...>]
)
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

 out

—

names the output data table for the initial and final topological orders, and the matrices of parameter estimates, standard deviations, t values, and p-values.

 outDag

—

names the output table for the estimated directed acyclic graph (DAG).

 outIterHist

—

names the output table for the iteration history.

 outPath

—

names the output data table for the parents, children, and paths.

 outputTables

names

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

Parameter Descriptions

algorithm="MCV" | "TOP"

specifies the algorithm to be used for DAG structure learning.

DefaultTOP
MCV

specifies the minimizing conditional variance (MCV) algorithm.

TOP

specifies the topological order permutation (TOP) algorithm.

alphas=[double-1 <, double-2, ...>]

specifies a list of significance levels for selecting the parent sets or edges. If the list contains more than one element, several DAGs are included in the outdag parameter table, one for each alpha value in the parameter list.

Aliasalpha

display={displayTables}

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

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

gpu=True | False

when set to True, uses enabled graphics processing unit (GPU) functions, if possible.

AliasgpuEnabled
DefaultFalse

initMethod="DATA" | "RANDOM" | "VARIANCE"

specifies the method to use for determining the initial topological order.

DefaultVARIANCE
DATA

specifies that the initial topological order should match the order of variables in the data table.

RANDOM

specifies that the initial topological order should be random.

VARIANCE

specifies that the initial topological order should be based on the variance of variables.

maxIter=64-bit-integer

specifies the maximum number of iterations for searching the space.

Default200
Minimum value0

out={casouttable}

names the output data table for the initial and final topological orders, and the matrices of parameter estimates, standard deviations, t values, and p-values.

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

outDag={casouttable}

names the output table for the estimated directed acyclic graph (DAG).

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

outIterHist={casouttable}

names the output table for the iteration history.

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

AliasoutIter

outPath={casouttable}

names the output data table for the parents, children, and paths.

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

AliasoutP

outputTables={outputTables}

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

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

AliasdisplayOut

parallel=True | False

when set to True, uses multithreading for the algorithm in searching the space.

DefaultTrue

seed=64-bit-integer

specifies a nonnegative integer to be used as the seed for generating random number sequences.

Default1
Minimum value0

* table={castable}

specifies the input data table.

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

Aliasdata

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

specifies a list of input variables in the input data table.

Aliasinputs

dagdiscovery Action

Performs directed acyclic graph (DAG) structure learning.

R Syntax

Développer toutRéduire tout
results <– cas.causalDiscovery.dagdiscovery(s,
algorithm="MCV" | "TOP",
alphas=list(double-1 <, double-2, ...>),
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
),
gpu=TRUE | FALSE,
initMethod="DATA" | "RANDOM" | "VARIANCE",
maxIter=64-bit-integer,
out
=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", ...>)
),
outDag
=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", ...>)
),
outIterHist
=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", ...>)
),
outPath
=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", ...>)
),
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
),
parallel=TRUE | FALSE,
seed=64-bit-integer,
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",
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"
)
),
required parameter vars=list("variable-name-1" <, "variable-name-2", ...>)
)
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

 out

—

names the output data table for the initial and final topological orders, and the matrices of parameter estimates, standard deviations, t values, and p-values.

 outDag

—

names the output table for the estimated directed acyclic graph (DAG).

 outIterHist

—

names the output table for the iteration history.

 outPath

—

names the output data table for the parents, children, and paths.

 outputTables

names

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

Parameter Descriptions

algorithm="MCV" | "TOP"

specifies the algorithm to be used for DAG structure learning.

DefaultTOP
MCV

specifies the minimizing conditional variance (MCV) algorithm.

TOP

specifies the topological order permutation (TOP) algorithm.

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

specifies a list of significance levels for selecting the parent sets or edges. If the list contains more than one element, several DAGs are included in the outdag parameter table, one for each alpha value in the parameter list.

Aliasalpha

display=list(displayTables)

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

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

gpu=TRUE | FALSE

when set to True, uses enabled graphics processing unit (GPU) functions, if possible.

AliasgpuEnabled
DefaultFALSE

initMethod="DATA" | "RANDOM" | "VARIANCE"

specifies the method to use for determining the initial topological order.

DefaultVARIANCE
DATA

specifies that the initial topological order should match the order of variables in the data table.

RANDOM

specifies that the initial topological order should be random.

VARIANCE

specifies that the initial topological order should be based on the variance of variables.

maxIter=64-bit-integer

specifies the maximum number of iterations for searching the space.

Default200
Minimum value0

out=list(casouttable)

names the output data table for the initial and final topological orders, and the matrices of parameter estimates, standard deviations, t values, and p-values.

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

outDag=list(casouttable)

names the output table for the estimated directed acyclic graph (DAG).

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

outIterHist=list(casouttable)

names the output table for the iteration history.

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

AliasoutIter

outPath=list(casouttable)

names the output data table for the parents, children, and paths.

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

AliasoutP

outputTables=list(outputTables)

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

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

AliasdisplayOut

parallel=TRUE | FALSE

when set to True, uses multithreading for the algorithm in searching the space.

DefaultTRUE

seed=64-bit-integer

specifies a nonnegative integer to be used as the seed for generating random number sequences.

Default1
Minimum value0

* table=list(castable)

specifies the input data table.

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

Aliasdata

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

specifies a list of input variables in the input data table.

Aliasinputs
Last updated: February 20, 2025