plvar.nls2 - Plot an nls2 Object for Studying the Variance Heterogeneity


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DESCRIPTION
USAGE
REQUIRED-ARGUMENTS
OPTIONAL-ARGUMENTS
CONSTRAINTS
DETAILS
SEE-ALSO
EXAMPLE



DESCRIPTION:

Plot the components of an `nls2.object' that may help the study of the variance heterogeneity when there are data replications.


USAGE:
plvar.nls2(nls2.object,
  step=nls2.object$nb.steps, 
  wanted=list(X.S2=T, X.S=F, logX.logS2=F, 
              Y.S2=T, Y.S=F, logY.logS2=F), 
  fitted=F, 
  n.fitted=0,
  smooth=F, labels=NULL, title="", figs=c(2, 2), 
  ask.pause=T, ask.modify=F, ...)

REQUIRED ARGUMENTS:
nls2.object
an object of class `nls2'.

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OPTIONAL ARGUMENTS:

step
when the nls2.object has been created by an alternated method of estimation, the index of the step requested. By default, the last step.
wanted
a list that specifies the graphs requested; Its components are logics that should be TRUE if the corresponding graphs are requested.
"wanted" components and their meanings are:
X.S2: the empirical variances are plotted against the independent variables.
X.S: the square roots of the empirical variances are plotted against the independent variables.
logX.logS2: the logarithms of the empirical variances are plotted against the logarithms of the independent variables.
Y.S2: the empirical variances are plotted against the empirical means. If the argument `fitted' is also set, the fitted variances are plotted against the fitted values of the regression function on the same graphs.
Y.S: the square roots of the empirical variances are plotted against the empirical means. If the argument `fitted' is also set, the square roots of the fitted variances are plotted against the fitted values of the regression function on the same graphs.
logY.logS2: the logarithms of the empirical variances are plotted against the logarithms of the means. If the argument `fitted' is also set, the logarithms of the fitted variances are plotted against the logarithms of the fitted values of the regression function on the same graphs.
fitted
a logic that should be TRUE if the fitted values of the variance should also be plotted. The points of the fitted values are joined by lines of different types if there are several curves.
n.fitted
if positive, this argument implies automatically that the argument `fitted' is TRUE and that function `loadnls2' has been previously called.
It is the number of regularly spaced points on the x-axis where the variance or regression functions are calculated for improving the fitted curves.
if the argument `n.fitted' is null and the argument `fitted' is TRUE, only the fitted values stored in `nls2.object' (see `nls2.object', component `response') are taken into account.
It is available only when there is one single variable.
smooth
a logic that should be TRUE if the points of the empirical variances should be joined. If so, they are joined by a dotted line after smoothing.
labels,title,figs,ask.pause,ask.modify,...

See `pldnls2'. According to the user's preference, the length of the "labels" vector is equal to the number of observations, either with replications and null-weighted observations included, or not included.

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CONSTRAINTS:

- A graphical device should have been previously activated.

- The data frame containing the observations must be available, (its name is nls2.object$call$data). It is then assumed that this data frame has been neither deleted nor modified since the nls2.object was created.
It must contain replications.


DETAILS:

This function is a method for the generic function `plvar' for class `nls2'. It can be invoked by calling `plvar' for an object of the appropriate class, or directly by calling `plvar.nls2' regardless of the class of the object.


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SEE ALSO:




EXAMPLE:
 X11()
 par(cex=2)
 plvar(nls2.out,fitted=T,
     labels=row.names(data),
     title="Data cortisol: plvar")

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- Mon Sep 30 1996 -