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:
qi = NED( (i-0.375) / (n+0.25) )
while for a half-Normal plot they are given by
qi = 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