predplot | R Documentation |
Functions to plot predicted values against measured values for a fitted model.
predplot(object, ...)
## Default S3 method:
predplot(object, ...)
## S3 method for class 'mvr'
predplot(
object,
ncomp = object$ncomp,
which,
newdata,
nCols,
nRows,
xlab = "measured",
ylab = "predicted",
main,
ask = nRows * nCols < nPlots && dev.interactive(),
...,
font.main,
cex.main
)
predplotXy(
x,
y,
line = FALSE,
labels,
type = "p",
main = "Prediction plot",
xlab = "measured response",
ylab = "predicted response",
line.col = par("col"),
line.lty = NULL,
line.lwd = NULL,
...
)
object |
a fitted model. |
... |
further arguments sent to underlying plot functions. |
ncomp |
integer vector. The model sizes (numbers of components) to use for prediction. |
which |
character vector. Which types of predictions to plot. Should
be a subset of |
newdata |
data frame. New data to predict. |
nCols , nRows |
integer. The number of coloumns and rows the plots will
be laid out in. If not specified, |
xlab , ylab |
titles for |
main |
optional main title for the plot. See Details. |
ask |
logical. Whether to ask the user before each page of a plot. |
font.main |
font to use for main titles. See |
cex.main |
numeric. The magnification to be used for main titles relative to the current size. Also see Details below. |
x |
numeric vector. The observed response values. |
y |
numeric vector. The predicted response values. |
line |
logical. Whether a target line should be drawn. |
labels |
optional. Alternative plot labels to use. Either a vector of
labels, or |
type |
character. What type of plot to make. Defaults to |
line.col , line.lty , line.lwd |
character or numeric. The |
predplot
is a generic function for plotting predicted versus measured
response values, with default and mvr
methods currently implemented.
The default method is very simple, and doesn't handle multiple responses or
new data.
The mvr
method, handles multiple responses, model sizes and types of
predictions by making one plot for each combination. It can also be called
through the plot method for mvr
, by specifying plottype =
"prediction"
(the default).
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 ‘global’ title on the page. Any graphical
parametres, e.g., cex.main
, supplied to coefplot
will only
affect the ‘ordinary’ plot titles, not the ‘global’ one. Its
appearance can be changed by setting the parameters with par
,
which will affect both titles (with the exception of font.main
and cex.main
, which will only affect the ‘global’ title when
there is more than one plot). (To have different settings for the two
titles, one can override the par
settings with arguments to
predplot
.)
predplotXy
is an internal function and is not meant for interactive
use. It is called by the predplot
methods, and its arguments, e.g,
line
, can be given in the predplot
call.
The functions invisibly return a matrix with the (last) plotted data.
The font.main
and cex.main
must be (completely) named.
This is to avoid that any argument cex
or font
matches them.
Tip: If the labels specified with labels
are too long, they get
clipped at the border of the plot region. This can be avoided by supplying
the graphical parameter xpd = TRUE
in the plot call.
Ron Wehrens and Bjørn-Helge Mevik
mvr
, plot.mvr
data(yarn)
mod <- plsr(density ~ NIR, ncomp = 10, data = yarn[yarn$train,], validation = "CV")
## Not run:
predplot(mod, ncomp = 1:6)
plot(mod, ncomp = 1:6) # Equivalent to the previous
## Both cross-validated and test set predictions:
predplot(mod, ncomp = 4:6, which = c("validation", "test"),
newdata = yarn[!yarn$train,])
## End(Not run)
data(oliveoil)
mod.sens <- plsr(sensory ~ chemical, ncomp = 4, data = oliveoil)
## Not run: plot(mod.sens, ncomp = 2:4) # Several responses gives several plots
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