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# resvsyhat()

Usage:
 ```resvsyhat([varNo,] [usehii:T or F] [graphics keyword phrases]), varNo a positive integer <= ncols(RESIDUALS) ```

Keywords: plotting, glm, residuals, anova, regression
```resvsyhat([graphics keyword phrases]) plots standardized residuals
against fitted or predicted values.

resvsyhat(usehii:F [,graphics keyword phrases]) does the same without
using leverages HII in standardizing.  The default is to use HII.

resvsyhat(standres:F [,graphics keyword phrases]) does the same without
any standardization.

The residuals are from variable RESIDUALS or WTDRESIDUALS produced by
the most recent GLM (generalized linear or linear model) command such as
regress(), anova(), or poisson().

If the most recent command was manova(), only column 1 of the residual
matrix is plotted.

resvsyhat() cannot be used to make a residual plot after an ARIMA fit
using macro arima().

resvsyhat(varNo [, usehii:T or F] [, standres:F] [,graphics keyword
phrases]), where varNo is an integer between 1 and ncols(RESIDUALS),
plots residuals associated with variable varNo against case numbers.
varNo > 1 is legal only when RESIDUALS was computed by manova().

The default plotting symbol is the same as for plot(), a drawn asterisk
or star ("\6").  You can change it by including 'symbols:c' as an
argument, where c is a CHARACTER or integer scalar or vector.  c = 0 is
special: it is equivalent to c = "###" and results in points being
labeled with case number.  See chplot(), subtopic 'symbols_used'.

You can use all the usual graphics keywords to modify the default plot
characteristics.  These include 'title', 'xlab', 'ylab', 'symbols'
'impulse' and 'lines'.  See topics 'graphs', 'graph_keys',
'graph_border' and 'graph_ticks'.

When you have set option 'dumbplot' to False (see 'options'), the plot
will be a low resolution plot unless 'dumb:F' is an argument.

Without standres:T, the quantities plotted are r[i]/sd[i] where r[i] is
RESIDUALS[i] or WTDRESIDUALS[i] and sd[i] is the estimated standard
deviation.  WTDRESIDUALS[i] is used after regress(), anova(), or
manova() with 'weights:wts' or after nonlinear GLM commands such as
logistic() and poisson().

When usehii is True (the default after GLM commands), sd[ii] =
sqrt(mse*(1-HII[i])), where mse is the residual mean square after
regress(), anova() or manova() or the mean error deviance after
non-linear GLM commands.

When usehii is False, sd[i] = sqrt(mse).

With standres:F, the quantities plotted are r[i].

The values on the X-axis are the estimated means of the response
variable.  After a nonlinear GLM command, they are in the original
scale, not the transformed scale.

resvsyhat() is implemented as macro.