mvr object.coefplot(object, ncomp = object$ncomp, comps, intercept = FALSE,
separate = FALSE, se.whiskers = FALSE, nCols, nRows, labels,
type = "l", lty, lwd = NULL, pch, cex = NULL, col, legendpos,
xlab = "variable", ylab = "regression coefficient", main,
pretty.xlabels = TRUE, xlim, ylim, ...)mvr object. The fitted model.coef.mvr for details.TRUE, coefficients for different model
sizes are blotted in separate plots.TRUE, whiskers at plus/minus
1 estimated standard error are added to the plot. This is only available if
the model was cross-validated with jackknife = TRUE. Also, in the
current implementation, icomps is specified. Defaults to
FALSE. See coef.mvr for details.coefplot tries
to be intelligent."l" (lines). Alternative types include "p" (points)
and "b" (both). See plot for a complete list
of typepar
for the details).points for all alternatives.par for the details.separate is
TRUE. If present, a legend is drawn at the given position.
The position can be specified symbolically (e.g., legendpos =
"topright"). This requires expression(R^2) or lists. See title for details.TRUE, coefplot
tries to plot the $x$ labels more nicely. See Details.coefplot handles multiple responses by making one plot for each
response. If separate is TRUE, separate plots are made
for each combination of model size and response. The plots are laid
out in a rectangular fashion. If legendpos is given, a legend is drawn at the given position
(unless separate is TRUE).
The argument labels can be a vector of labels or one of
"names" and "numbers". The labels are
used as $x$ axis labels. If labels is "names" or
"numbers", the variable names are used as labels, the
difference being that with "numbers", the variable names are
converted to numbers, if possible. Variable names of the forms
"number" or "number text" (where the space is optional),
are handled.
The argument main can be used to specify the main title of the
plot. It is handled in a non-standard way. If there is only on (sub)
plot, main will be used as the main title of the plot. If
there is more than one (sub) plot, however, the presence of
main will produce a corresponding cex.main, supplied to
coefplot will only affect the par, which will affect both
titles. (To have different settings for the two titles, one can
override the par settings with arguments to coefplot.)
The argument pretty.xlabels is only used when labels is
specified. If TRUE (default), the code tries
to use a labels is
"numbers", it also uses the numerical values of the labels for
horisontal spacing. If one has excluded parts of the spectral
region, one might therefore want to use pretty.xlabels = FALSE.
When separate is TRUE, the arguments lty,
col, and pch default to their par() setting.
Otherwise, the default for all of them is 1:nLines, where
nLines is the number of model sizes specified, i.e., the length
of ncomp or comps.
The function can also be called through the mvr plot method by
specifying plottype = "coefficients".
mvr, plot.mvr, coef.mvr,
plot, legenddata(yarn)
mod.nir <- plsr(density ~ NIR, ncomp = 8, data = yarn)
coefplot(mod.nir, ncomp = 1:6)
plot(mod.nir, plottype = "coefficients", ncomp = 1:6) # Equivalent to the previous
## Plot with legend:
coefplot(mod.nir, ncom = 1:6, legendpos = "bottomright")
data(oliveoil)
mod.sens <- plsr(sensory ~ chemical, ncomp = 4, data = oliveoil)
coefplot(mod.sens, ncomp = 2:4, separate = TRUE)Run the code above in your browser using DataLab