19 Not Implemented
This chapter lists parts of the pspp language that are not yet
implemented.
2SLS- Two stage least squares regression
ACF- Autocorrelation function
ALSCAL- Multidimensional scaling
ANACOR- Correspondence analysis
ANOVA- Factorial analysis of variance
CASEPLOT- Plot time series
CASESTOVARS- Restructure complex data
CATPCA- Categorical principle components analysis
CATREG- Categorical regression
CCF- Time series cross correlation
CLEAR TRANSFORMATIONS- Clears transformations from active dataset
CLUSTER- Hierarchical clustering
CONJOINT- Analyse full concept data
CORRESPONDENCE- Show correspondence
COXREG- Cox proportional hazards regression
CREATE- Create time series data
CSDESCRIPTIVES- Complex samples descriptives
CSGLM- Complex samples GLM
CSLOGISTIC- Complex samples logistic regression
CSPLAN- Complex samples design
CSSELECT- Select complex samples
CSTABULATE- Tabulate complex samples
CTABLES- Display complex samples
CURVEFIT- Fit curve to line plot
DATE- Create time series data
DEFINE- Syntax macros
DETECTANOMALY- Find unusual cases
DISCRIMINANT- Linear discriminant analysis
EDIT- obsolete
END FILE TYPE- Ends complex data input
FILE TYPE- Complex data input
FIT- Goodness of Fit
GENLOG- Categorical model fitting
GET TRANSLATE- Read other file formats
GGRAPH- Custom defined graphs
HILOGLINEAR- Hierarchical loglinear models
HOMALS- Homogeneity analysis
IGRAPH- Interactive graphs
INFO- Local Documentation
KEYED DATA LIST- Read nonsequential data
KM- Kaplan-Meier
LOGLINEAR- General model fitting
MANOVA- Multivariate analysis of variance
MAPS- Geographical display
MATRIX- Matrix processing
MATRIX DATA- Matrix data input
MCONVERT- Convert covariance/correlation matrices
MIXED- Mixed linear models
MODEL CLOSE- Close server connection
MODEL HANDLE- Define server connection
MODEL LIST- Show existing models
MODEL NAME- Specify model label
MULTIPLE CORRESPONDENCE- Multiple correspondence analysis
MULT RESPONSE- Multiple response analysis
MVA- Missing value analysis
NAIVEBAYES- Small sample bayesian prediction
NLR- Non Linear Regression
NOMREG- Multinomial logistic regression
NONPAR CORR- Nonparametric correlation
NUMBERED-
OLAP CUBES- On-line analytical processing
OMS- Output management
ORTHOPLAN- Orthogonal effects design
OVERALS- Nonlinear canonical correlation
PACF- Partial autocorrelation
PARTIAL CORR- Partial correlation
PLANCARDS- Conjoint analysis planning
PLUM- Estimate ordinal regression models
POINT- Marker in keyed file
PPLOT- Plot time series variables
PREDICT- Specify forecast period
PREFSCAL- Multidimensional unfolding
PRINCALS- PCA by alternating least squares
PROBIT- Probit analysis
PROCEDURE OUTPUT- Specify output file
PROXIMITIES- Pairwise similarity
PROXSCAL- Multidimensional scaling of proximity data
RATIO STATISTICS- Descriptives of ratios
READ MODEL- Read new model
RECORD TYPE- Defines a type of record within FILE TYPE
REFORMAT- Read obsolete files
REPEATING DATA- Specify multiple cases per input record
REPORT- Pretty print working file
RMV- Replace missing values
SCRIPT- Run script file
SEASON- Estimate seasonal factors
SELECTPRED- Select predictor variables
SPCHART- Plot control charts
SPECTRA- Plot spectral density
STEMLEAF- Plot stem-and-leaf display
SUMMARIZE- Univariate statistics
SURVIVAL- Survival analysis
TDISPLAY- Display active models
TREE- Create classification tree
TSAPPLY- Apply time series model
TSET- Set time sequence variables
TSHOW- Show time sequence variables
TSMODEL- Estimate time series model
TSPLOT- Plot time sequence variables
TWOSTEP CLUSTER- Cluster observations
UNIANOVA- Univariate analysis
UNNUMBERED- obsolete
VALIDATEDATA- Identify suspicious cases
VARCOMP- Estimate variance
VARSTOCASES- Restructure complex data
VERIFY- Report time series
WLS- Weighted least squares regression
XGRAPH- High resolution charts