glpls1a.mlogit.cv.error: Leave-one-out cross-validation error using MIRWPLS and MIRWPLSF model

Description

Leave-one-out cross-validation training set error for fitting MIRWPLS or MIRWPLSF model for multi-group classification

Usage

glpls1a.mlogit.cv.error(train.X, train.y, K.prov = NULL, eps = 0.001,lmax = 100, mlogit = T, br = T)

Arguments

train.X

n by p design matrix (with no intercept term) for training set

train.y

response vector with class lables 1 to C+1 for C+1 group classification, baseline class should be 1

K.prov

number of PLS components

eps

tolerance for convergence

lmax

maximum number of iteration allowed

mlogit

if TRUE use the multinomial logit model, otherwise fit all C-1 logistic models (vs baseline class 1) separately

TRUE if Firth's bias reduction procedure is used

Value

error: LOOCV training error
error.obs: the misclassified error observation indices

References

Ding, B.Y. and Gentleman, R. (2003) Classification using generalized partial least squares.
Marx, B.D (1996) Iteratively reweighted partial least squares estimation for generalized linear regression. Technometrics 38(4): 374-381.

Examples

Run this code

 x <- matrix(rnorm(20),ncol=2)
 y <- sample(1:3,10,TRUE)

 ## no bias reduction
 glpls1a.mlogit.cv.error(x,y,br=FALSE)
 glpls1a.mlogit.cv.error(x,y,mlogit=FALSE,br=FALSE)
 ## bias reduction
 glpls1a.mlogit.cv.error(x,y,br=TRUE)
 glpls1a.mlogit.cv.error(x,y,mlogit=FALSE,br=TRUE)

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