proc cas; pca.eig / table={name="iris", caslib="casuser"} /* Use specific numeric inputs */ inputs={"SepalLength", "SepalWidth", "PetalLength", "PetalWidth"} /* Use Covariance matrix instead of Correlation */ cov=true /* Standardize scores to unit variance ...
proc cas; uniTimeSeries.esm / table={name="sales_data", caslib="casuser"} timeId={name="date"} interval="month" forecast={{name="sales", method="BEST", lead=12}}; run;
proc cas; uniTimeSeries.esm / table={name="sales_data", caslib="casuser"} timeId={name="date"} interval="month" forecast={{name="sales", method="WINTERS", lead=12, alpha=0.05}} outFor={name="sales_forecast", caslib="casuser", replace=true} outStat={name="sales_stats", caslib="casuser", replace=tr...
proc cas; spc.ewmaChart / table={name="metalclips", caslib="mycas"} processValue="gap" subgroupValue="day"; run;
proc cas; spc.ewmaChart / table={name="metalclips", caslib="mycas"} processValue="gap" subgroupValue="day" weight=0.2 sigmas=3 outLimitsTable={name="ewma_limits", caslib="mycas", replace=true} chartsTable={name="ewma_summary", caslib="mycas", replace=true}; run;
proc cas; sparkEmbeddedProcess.executeProgram / caslib="sparkLib" program="println(\"Hello from Spark EP\")"; run;
proc cas; sparkEmbeddedProcess.executeProgram / caslib="sparkLib" programFile="/path/to/complex_logic.scala"; run;
proc cas; dataSciencePilot.exploreCorrelation / table={name="correlation_data", caslib="casuser"} target="c"; run;
proc cas; dataSciencePilot.exploreCorrelation / table={name="correlation_data", caslib="casuser"} target="c" binMissing=true misraGries=false stats={ intervalInterval={"PEARSON", "MI"}, nominalInterval={"MI", "SU"} } casOut=...
proc cas; astore.extract / rstore={name="onnx_store", caslib="casuser"}; run;