Output objects from package relaimpo have classes
relimplm (output from calc.relimp),
(output from boot.relimp),
relimplmbooteval (output from booteval.relimp) or
relimplmbootMI, there are methods for plotting and printing,
usage of which is described below. For class
relimplmbootMI, there is in addition a summary-method,
which produces a less detailed output than the show / print - method.
there is in addition a method for extracting slots of the class with \$.
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## S3 method for class 'relimplm' print(x,...,show.coeffs = ifelse(any(c("lmg", "pmvd") %in% x@type) & is.null(x@always), TRUE, FALSE)) ## S3 method for class 'relimplm' plot(x,...,names.abbrev=4, ylim=NULL, main=NULL, cex.title=1.5) ## S3 method for class 'relimplmbooteval' print(x,...) ## S3 method for class 'relimplmbootMI' print(x,...) ## S3 method for class 'relimplmbooteval' plot(x, ..., lev=max(x@level), names.abbrev=4, ylim=NULL, main=NULL, cex.title=1.5) ## S3 method for class 'relimplmbootMI' plot(x, ..., lev=max(x@level), names.abbrev=4, ylim=NULL, main=NULL, cex.title=1.5) ## S3 method for class 'relimplmbootMI' summary(object, ..., lev = max(object@level))
further arguments to functions
The plot routines try to use appropriate scaling. If adjustments are needed,
The plot routine uses a default title based on the reponses name.
If adjustments are desired,
This documentation part describes S3 methods. In addition there are S4 methods for
coincide with the S3 methods for
relimplm to lists
(of their numeric elements).
Print (and show) methods produce annotated output for
mianalyze.relimp (or the objects produced by these functions). Since version 2.1,
provides averaged coefficients for different sub model sizes (slot
ave.coeffs of class
if metrics based on averaging over orderings (
pmvd) are calculated.
These are per default printed if the slot
If some variables were forced into all models (non-NULL
always), the averaged coefficients
refer to the adjusted model after taking residuls from regressions on the
of the X-matrix for both response and the other columns of the X-matrix. The reason is that these could be
easily and cheaply implemented into the existing code and do correspond to sub models relevant
pmvd. Users who are interested in these coefficients, can set option
in spite of non-NULL
The plot methods produce barplots of relative contributions,
either of the metrics alone for output objects of class
relimplm from function
or of the metrics with lines indicating confidence intervals for output objects of class
relimplmbootMI from function
par() options can be set and should work on plot.
Exceptions: mfrow, oma and mar are set by the plot function,
depending on the number of metrics to plot and the amount of annotating text required.
The summary-method for class
relimplmbootMI allows to quickly display brief output and to change
the confidence level versus the level used in the original run (with interval bounds stored in the
“metric”.lower and “metric”.upper slots and displayed by print and show methods).
Because of a defined S3-extraction method,
slots of classes
relimplmbootMI can be extracted not only
with the @ extractor but also with \$.
Hence, output elements from functions
can be extracted as though the output objects were lists.
Note that there also is an an internally-used class relimplmtest that permits the internal function calc.relimp.default.intern to output further detail needed for usage from within other funtions.
Ulrike Groemping, BHT Berlin
Go to http://prof.tfh-berlin.de/groemping/ for further information and references.
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