plot.nnreg {funfits}R Documentation

Diagnoistic and summary plots of a neural net regression object

Description

This function creates four summary plots of the tps object. The first plot is a plot of the nnreg fit to the data. The second is predicted values vs residuals. The third is number of parameters vs GCV with cost=1 and cost=2. The fourth plot is number of parameters vs root mean squared error.

Usage

plot.nnreg(out, model=out$best.model, main=NA, digits=4, graphics.reset=T, ...)

Arguments

out A nnreg object
model Model number to plot. Default is the best model based on GCV(2).
main Title of the plot. Default is the function call.
digits Number of significant digits for the RMSE label.
graphics.reset Reset to original graphics parameters after function plotting.
... Any plotting arguments.

See Also

nnreg, summary.nnreg

Examples

nnreg(ozone$x,ozone$y,1,2) -> fit # fitting a surface to ozone 
# measurements, from 1 to 2 hidden units
plot(fit) # plots fit and residuals

nnreg(as.matrix(BD[,1:4]),BD[,5],1,5) -> fit # fitting DNA strand
# displacement amplification surface to various buffer compositions
plot(fit) # plots fit and residuals

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