<!doctype s-function-doc system "s-function-doc.dtd" [
<!entity % S-OLD "INCLUDE">
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<s-function-doc>
<s-topics>
   <s-topic>plot.lmRob</s-topic>
</s-topics>

<s-title>
Diagnostic Plots for Robustly Fitted Linear Models
</s-title>

<s-description>
Creates a set of plots suitable for assessing a robustly fitted linear  
model of class lmRob.  The plot options are (2) Normal QQ-Plot of
Residuals, (3) Estimated Kernel Density of Residuals, (4) Robust Residuals
vs Robust Distances, (5) Residuals vs Fitted Values, (6) Sqrt of
abs(Residuals) vs Fitted Values, (7) Response vs Fitted Values, (8)
Standardized Residuals vs Index (Time), (9) Overlaid Normal QQ-Plot of
Residuals, and (10) Overlaid Estimated Density of Residuals.
</s-description>

<s-usage>
<s-old-style-usage>
plot.lmRob(x, which.plots = "ask", chisq.percent = 0.99, vertical.outlier =
0.99, smooths = F, rugplot = F, id.n = 3, envelope = T, half.normal =
F,robustQQline = T, mc.samples = 100, level = 0.95, seed = 289, cutoff = T,
...)
</s-old-style-usage>
</s-usage>

<s-args-required>
<s-arg name=" x ">
an lmRob object.
</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=" 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-arg name=" envelope ">
if TRUE, a simulation envelope is added to the QQ-plot.
</s-arg>

<s-arg name=" half.normal ">
if TRUE, half normal QQ-plots will be used.
</s-arg>

<s-arg name=" robustQQline ">
if TRUE a robust fit is added to the QQ-plot.
</s-arg>

<s-arg name=" mc.samples ">
number of samples used in computing the simulation envelope.
</s-arg>

<s-arg name=" level ">
confidence level for the simulation envelope.
</s-arg>

<s-arg name=" seed ">
an integer between 0 and 1023.  The seed value used for random number
generation in the QQ-plot simulation envelope.
</s-arg>

<s-arg name=" cutoff ">
if TRUE, bounds are added to the one variable regression plot.
Observations outside these bounds received zero weight in the analysis.
</s-arg>
</s-args-optional>

<s-side-effects>
The selected plots are drawn on a graphics device.
</s-side-effects>

<s-details>
If the model has exactly one explanatory variable then there is the
additional option to plot the fit over a scatter plot of the data.
<br><br>
The lmRob object is coerced to an lmfm object containing a single
model. The plotting is then accomplished by calling plot.lmfm.
</s-details>

<s-see>
<s-function name="plot.sgm">plot</s-function>,
<s-function name="plot.lmfm.sgm">plot.lmfm</s-function>.
</s-see>

<s-keywords>
<s-keyword>robust</s-keyword>
<s-keyword>models</s-keyword>
<s-keyword>regression</s-keyword>
<s-keyword>librobust</s-keyword>
</s-keywords>

<s-docclass>
function
</s-docclass>

</s-function-doc>
