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18 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

GRAPH

Draw 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

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


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