{gpls}R Documentation

Leave-one-out cross-validation error using MIRWPLS and MIRWPLSF model


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

Usage, train.y, K.prov = NULL, eps = 0.001,lmax = 100, mlogit = T, br = T)


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
br TRUE if Firth's bias reduction procedure is used



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



Beiying Ding, Robert Gentleman


  • 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.

    See Also, glpls1a.train.test.error,glpls1a, glpls1a.mlogit,glpls1a.logit.all


     x <- matrix(rnorm(20),ncol=2)
     y <- sample(1:3,10,TRUE)
     ## no bias reduction,y,br=FALSE),y,mlogit=FALSE,br=FALSE)
     ## bias reduction,y,br=TRUE),y,mlogit=FALSE,br=TRUE)

    [Package gpls version 1.0.6 Index]