a data.frame containing the design and the response of a test set when available, the prediction criteria will be computed for the test data (default corresponds to no test set)
graphic
if TRUE the values of the criteria are represented
K
the number of folds for cross-validation (by default, K=10)
Penalty
a vector containing the values of the penalty parameter
Value
A data frame containing
a
the values of the penalty parameter
R2
the R2 criterion evaluted on the learning set
m
the size of the selected model
If a test set is available the last row is
R2test
the R2 criterion evaluated on the test set
If no test set is available, criteria computed by K-corss-validation are provided:
Q2
the Q2 evaluated by cross-validation (by default, K=10)
RMSE CV
RMSE computed by cross-validation
Note that the penalty parameter could be chosen by minimizing the value of the RMSE by cross-validation.
Author(s)
D. Dupuy
See Also
modelFit, R2 and crossValidation
Examples
data(dataIRSN5D)
X <- dataIRSN5D[,1:5]
Y <- dataIRSN5D[,6]
data(testIRSN5D)
library(polspline)
Crit <- penaltyPolyMARS(X,Y,test=testIRSN5D[,-7],graphic=TRUE)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(DiceEval)
Loading required package: DiceKriging
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/DiceEval/penaltyPolyMARS.Rd_%03d_medium.png", width=480, height=480)
> ### Name: penaltyPolyMARS
> ### Title: Choice of the penalty parameter for a PolyMARS model
> ### Aliases: penaltyPolyMARS
> ### Keywords: models
>
> ### ** Examples
>
> data(dataIRSN5D)
> X <- dataIRSN5D[,1:5]
> Y <- dataIRSN5D[,6]
> data(testIRSN5D)
> library(polspline)
> Crit <- penaltyPolyMARS(X,Y,test=testIRSN5D[,-7],graphic=TRUE)
>
>
>
>
>
> dev.off()
null device
1
>