glpls1a.train.test.error: out-of-sample test set error using IRWPLS and IRWPLSF model

In gpls: Classification using generalized partial least squares

Description

Out-of-sample test set error for fitting IRWPLS or IRWPLSF model on the training set for two-group classification

Usage

glpls1a.train.test.error(train.X,train.y,test.X,test.y,K.prov=NULL,eps=1e-3,lmax=100,family="binomial",link="logit",br=T)

Arguments

train.X	n by p design matrix (with no intercept term) for training set
train.y	response vector (0 or 1) for training set
test.X	transpose of the design matrix (with no intercept term) for test set
test.y	response vector (0 or 1) for test set
K.prov	number of PLS components, default is the rank of train.X
eps	tolerance for convergence
lmax	maximum number of iteration allowed
family	glm family, binomial is the only relevant one here
link	link function, logit is the only one practically implemented now
br	TRUE if Firth's bias reduction procedure is used

Value

error	out-of-sample test error
error.obs	the misclassified error observation indices
predict.test	the predicted probabilities for test set

Author(s)

Beiying Ding, Robert Gentleman

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.

See Also

glpls1a.cv.error, glpls1a.mlogit.cv.error, glpls1a, glpls1a.mlogit, glpls1a.logit.all

Examples

 x <- matrix(rnorm(20),ncol=2)
 y <- sample(0:1,10,TRUE)
 x1 <- matrix(rnorm(10),ncol=2)
 y1 <- sample(0:1,5,TRUE)

 ## no bias reduction
 glpls1a.train.test.error(x,y,x1,y1,br=FALSE)
 ## bias reduction
 glpls1a.train.test.error(x,y,x1,y1,br=TRUE)

gpls documentation built on Nov. 8, 2020, 6:50 p.m.