| coefplot {pls} | R Documentation |
Function to plot the regression coefficients of an mvr object.
coefplot(object, ncomp = object$ncomp, separate = FALSE, cumulative = TRUE,
intercept = FALSE, nCols, nRows, type = "l", ...)
object |
an mvr object. The fitted model. |
ncomp |
integer vector. The number of components to include. If
length(ncomp) > 1, coefficients for each model size is plotted. |
separate |
logical. If TRUE, coefficients for different model
sizes are blotted in separate plots. |
cumulative |
logical. Whether cumulative (the default) or
individual coefficients for each component should be plotted. See
coef.mvr for details. |
intercept |
logical. Whether coefficients for the intercept should
be plotted. Ignored if cumulative = FALSE. Defaults to
FALSE. See coef.mvr for details. |
nCols, nRows |
integer. The number of coloumns and rows the
plots will be laid out in. If not specified, coefplot tries
to be intelligent. |
type |
character. What type of plot to make. Defaults to
"l" (lines). See plot for details. |
... |
Further arguments sent to the underlying plot functions. |
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.
The function can also be called through the mvr plot method by
specifying plottype = "coefficients".
Ron Wehrens and Bjørn-Helge Mevik
data(NIR) mod.nir <- plsr(y ~ X, ncomp = 8, data = NIR) ## Not run: coefplot(mod.nir, ncomp = 1:6) plot(mod.nir, plottype = "coefficients", ncomp = 1:6) # Equivalent to the previous ## End(Not run) data(sensory) mod.sens <- plsr(Quality ~ Panel, ncomp = 4, data = sensory) ## Not run: plot(mod.sens, ncomp = 2:4, separate = TRUE)