pls (version 2.1-0)

validationplot: Validation Plots

Description

Functions to plot validation statistics, such as RMSEP or $R^2$, as a function of the number of components.

Usage

validationplot(object, val.type = c("RMSEP", "MSEP", "R2"), estimate,
               newdata, ncomp, comps, intercept, ...)
## S3 method for class 'mvrVal':
plot(x, nCols, nRows, type = "l", lty = 1:nEst, lwd = NULL,
           pch = 1:nEst, cex = NULL, col = 1:nEst, legendpos,
           xlab = "number of components", ylab = x$type, main, \dots)

encoding

latin1

Details

validationplot calls the proper validation function (currently MSEP, RMSEP or R2) and plots the results with plot.mvrVal. validationplot can be called through the mvr plot method, by specifying plottype = "validation".

plot.mvrVal creates one plot for each response variable in the model, laid out in a rectangle. It uses matplot for performing the actual plotting. If legendpos is given, a legend is drawn at the given position.

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. (To have different settings for the two titles, one can override the par settings with arguments to the plot function.)

See Also

mvr, plot.mvr, RMSEP, MSEP, R2, matplot, legend

Examples

data(oliveoil)
mod <- plsr(sensory ~ chemical, data = oliveoil, validation = "LOO")
## These three are equivalent:
validationplot(mod, estimate = "all")
plot(mod, "validation", estimate = "all")
plot(RMSEP(mod, estimate = "all"))
## Plot R2:
plot(mod, "validation", val.type = "R2")
## Plot R2, with a legend:
plot(mod, "validation", val.type = "MSEP", legendpos = "top") # R >= 2.1.0