glpls1a.mlogit.cv.error: Leave-one-out cross-validation error using MIRWPLS and...
In gpls: Classification using generalized partial least squares

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/glpls1a.error.R

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

1	glpls1a.mlogit.cv.error(train.X, 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.

glpls1a.cv.error, 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
 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)