This chapter lists parts of the PSPP language that are not yet implemented.
2SLSTwo stage least squares regression
ACFAutocorrelation function
ALSCALMultidimensional scaling
ANACORCorrespondence analysis
ANOVAFactorial analysis of variance
CASEPLOTPlot time series
CASESTOVARSRestructure complex data
CATPCACategorical principle components analysis
CATREGCategorical regression
CCFTime series cross correlation
CLEAR TRANSFORMATIONSClears transformations from active dataset
CLUSTERHierarchical clustering
CONJOINTAnalyse full concept data
CORRESPONDENCEShow correspondence
COXREGCox proportional hazards regression
CREATECreate time series data
CSDESCRIPTIVESComplex samples descriptives
CSGLMComplex samples GLM
CSLOGISTICComplex samples logistic regression
CSPLANComplex samples design
CSSELECTSelect complex samples
CSTABULATETabulate complex samples
CURVEFITFit curve to line plot
DATECreate time series data
DETECTANOMALYFind unusual cases
DISCRIMINANTLinear discriminant analysis
EDITobsolete
END FILE TYPEEnds complex data input
FILE TYPEComplex data input
FITGoodness of Fit
GENLOGCategorical model fitting
GET TRANSLATERead other file formats
GGRAPHCustom defined graphs
HILOGLINEARHierarchical loglinear models
HOMALSHomogeneity analysis
IGRAPHInteractive graphs
INFOLocal Documentation
KEYED DATA LISTRead nonsequential data
KMKaplan-Meier
LOGLINEARGeneral model fitting
MANOVAMultivariate analysis of variance
MAPSGeographical display
MIXEDMixed linear models
MODEL CLOSEClose server connection
MODEL HANDLEDefine server connection
MODEL LISTShow existing models
MODEL NAMESpecify model label
MULTIPLE CORRESPONDENCEMultiple correspondence analysis
MULT RESPONSEMultiple response analysis
MVAMissing value analysis
NAIVEBAYESSmall sample bayesian prediction
NLRNon Linear Regression
NOMREGMultinomial logistic regression
NONPAR CORRNonparametric correlation
NUMBEREDOLAP CUBESOn-line analytical processing
OMSOutput management
ORTHOPLANOrthogonal effects design
OVERALSNonlinear canonical correlation
PACFPartial autocorrelation
PARTIAL CORRPartial correlation
PLANCARDSConjoint analysis planning
PLUMEstimate ordinal regression models
POINTMarker in keyed file
PPLOTPlot time series variables
PREDICTSpecify forecast period
PREFSCALMultidimensional unfolding
PRINCALSPCA by alternating least squares
PROBITProbit analysis
PROCEDURE OUTPUTSpecify output file
PROXIMITIESPairwise similarity
PROXSCALMultidimensional scaling of proximity data
RATIO STATISTICSDescriptives of ratios
READ MODELRead new model
RECORD TYPEDefines a type of record within FILE TYPE
REFORMATRead obsolete files
REPEATING DATASpecify multiple cases per input record
REPORTPretty print working file
RMVReplace missing values
SCRIPTRun script file
SEASONEstimate seasonal factors
SELECTPREDSelect predictor variables
SPCHARTPlot control charts
SPECTRAPlot spectral density
STEMLEAFPlot stem-and-leaf display
SUMMARIZEUnivariate statistics
SURVIVALSurvival analysis
TDISPLAYDisplay active models
TREECreate classification tree
TSAPPLYApply time series model
TSETSet time sequence variables
TSHOWShow time sequence variables
TSMODELEstimate time series model
TSPLOTPlot time sequence variables
TWOSTEP CLUSTERCluster observations
UNIANOVAUnivariate analysis
UNNUMBEREDobsolete
VALIDATEDATAIdentify suspicious cases
VARCOMPEstimate variance
VARSTOCASESRestructure complex data
VERIFYReport time series
WLSWeighted least squares regression
XGRAPHHigh resolution charts