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

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

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

Details

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(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)

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