<!doctype s-function-doc system "s-function-doc.dtd" [
<!entity % S-OLD "INCLUDE">
]
>
<s-function-doc>
<s-topics>
<s-topic> plot.glmfm </s-topic>
</s-topics>
<s-title>
Comparison Plots for Generalized Linear Models
</s-title>
<s-description>
Creates a set plots useful for comparing fitted generalized linear models
stored in a class fit.models object belonging to virtual class glmfm.
The plot options are (2) Deviances vs Fitted Values, (3) Response vs Fitted
Values, (4) QQ-Plot of Pearson Residuals, (5) Deviances QQ-Plot, (6)
Standardized Deviances vs Robust Distances, (7) Standardized Deviances vs
Index (Time), and (8) Sqrt of abs(Deviances) vs Fitted Values.
</s-description>

<s-usage>
<s-old-style-usage>
plot.glmfm(x, which.plots="ask", type="pearson", chisq.percent=0.99,
           vertical.outlier=0.99, smooths=F, rugplot=F, id.n=3, ...)
</s-old-style-usage>
</s-usage>
<s-args-required>
<s-arg name=" x ">
a fit.models object belonging to virtual class glmfm.
</s-arg>
</s-args-required>
<s-args-optional>
<s-arg name=" which.plots ">
either "ask", "all", or an integer vector specifying which plots to
draw.
If <s-expression>which.plots</s-expression> is an integer vector,
use the plot numbers given in the description above (or in the "ask" menu).
</s-arg>
<s-arg name=" type ">
type of residuals, with choices "deviance", "pearson", "working" or
"response"; "pearson" is the default.
</s-arg>
<s-arg name=" chisq.percent ">
p-value used to calculate the chi-squared quantile used as the outlier
threshold for robust distances.
</s-arg>
<s-arg name=" vertical.outlier ">
p-value used to calculate the standard normal quantile used as the outlier
threshold for residuals.
</s-arg>
<s-arg name=" smooths ">
if TRUE, smooth curves are approximated to the scatterplots using
loess.smooth and added to the appropriate plots.
</s-arg>
<s-arg name=" rugplot ">
if TRUE, a univariate histogram or rugplot is displayed along the base of
each plot, showing the occurrence of each x-value; ties are broken by
jittering.
</s-arg>
<s-arg name=" id.n ">
number of outliers identified in plots.
</s-arg>
</s-args-optional>
<s-value>
x is invisibly returned.
</s-value>
<s-side-effects>
The selected plots are drawn on a graphics device.
</s-side-effects>
<s-see>
<s-function name="plot.sgm">plot</s-function>,
<s-function name="fit.models1.sgm">fit.models</s-function>.
</s-see>
<s-examples>
<s-example>
breslow.mle <- glm(sumY ~ Age10 + Base4 * Trt, family=poisson,
     data=breslow.dat)
breslow.rob <- glmRob(sumY ~ Age10 + Base4 * Trt, family=poisson,
     data=breslow.dat)
breslow.fm <- fit.models(breslow.rob, breslow.mle)
##
## breslow.fm is a fit.models object with virtual class glmfm.
##
plot(breslow.fm)
</s-example>
</s-examples>
<s-keywords>
<s-keyword>hplot</s-keyword>
<s-keyword>librobust</s-keyword>
</s-keywords>
<s-docclass>
function
</s-docclass>
</s-function-doc>
