DRESIDUALS procedure

Plots residuals (R.W. Payne).

Options

RESIDUALS = variate	Residuals to plot
FITTEDVALUES = variate	Fitted values against which to plot the residuals
INDEX = variate or factor	X-variable for an index plot; default !(1,2...)
GRAPHICS = string token	What type of graphics to use (lineprinter, highresolution); default high
TITLE = text	Overall title for the plots; default * i.e. none

Parameters

METHOD = string tokens	Type of residual plot (fittedvalues, normal, halfnormal, histogram, absresidual, index); default fitt, norm, half, hist
PEN = scalars, variates or factors	Pen(s) to use for each plot

Description

Procedure DRESIDUALS provides up to four types of plots of residuals. These are selected using the METHOD parameter, with settings: fitted for residuals versus fitted values, normal for a Normal plot, halfnormal for a half-Normal plot, histogram for a histogram of residuals, absresidual for a plot of the absolute values of the residuals versus the fitted values, and index for a plot against an “index” variable (specified by the INDEX option). The PEN parameter can specify the graphics pen or pens to use for each plot.

The residuals and fitted values must be supplied, in variates, using the RESIDUALS and FITTEDVALUES options, respectively. The TITLE option can supply an overall title for the plots. By default, high-resolution graphics are used. Line-printer graphics can be requested instead, by setting option GRAPHICS=lineprinter.

Options: RESIDUALS, FITTEDVALUES, INDEX, GRAPHICS, TITLE.

Parameters: METHOD, PEN.

Method

For a Normal plot, the Normal quantiles are calculated as follows:

q_i = NED( (i-0.375) / (n+0.25) )

while for a half-Normal plot they are given by

q_i = NED( 0.5 + 0.5 × (i-0.375) / (n+0.25) )

Action with RESTRICT

If the variates are restricted, only the units not excluded by the restriction will be included in the graphs.

See also

Procedures APLOT, RCHECK, VPLOT.

Commands for: Graphics.

Example

CAPTION 'DRESIDUALS example',\ 
        !t('Data from Snedecor & Cochran (1980), Statistical',\ 
        'Methods, (Iowa State University Press), page 305;',\ 
        'also see the Guide to Genstat, Part 2, Section 4.1.');\
        STYLE=meta,plain
FACTOR  [LABELS=!T(beef,cereal,pork); VALUES=(1...3)20] Source
&       [LABELS=!T(high,low); VALUES=3(1,2)10] Amount
VARIATE [NVALUES=60] Gain
READ Gain
 73  98  94  90 107  49
102  74  79  76  95  82
118  56  96  90  97  73
104 111  98  64  80  86
 81  95 102  86  98  81
107  88 102  51  74  97
100  82 108  72  74 106
 87  77  91  90  67  70
117  86 120  95  89  61
111  92 105  78  58  82 :
BLOCKSTRUCTURE
TREATMENTSTRUCTURE Source*Amount
ANOVA      [PRINT=aovtable] Gain; RESIDUALS=Residual; FITTEDVALUES=Fitted
DRESIDUALS [RESIDUALS=Residual; FITTEDVALUES=Fitted]\
           fittedvalues, normal, halfnormal, histogram
&          [GRAPHICS=lineprinter] fittedvalues, normal, halfnormal, histogram