pls (version 1.1-0)

validationplot: Validation Plots

Description

Functions to plot validation statistics, such as RMSEP or R2, as a function of the number of components.

Usage

validationplot(object, val.type = c("RMSEP", "MSEP", "R2"), estimate,
               newdata, 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, \dots)

Value

• If legendpos is given, the functions return whatever legend returns. Otherwise they do not return any values.

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.

See Also

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

Examples

data(sensory)
mod <- plsr(Panel ~ Quality, data = sensory, 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