pamr.cv {pamr}R Documentation

A function to cross-validate the nearest shrunken centroid classifier

Description

A function to cross-validate the nearest shrunken centroid classifier produced by pamr.train

Usage

pamr.cv(fit, data,  nfold = min(table(data$y)), folds = balanced.folds(data$y), ...)

Arguments

fit The result of a call to pamr.train
data A list with at least two components: x- an expression genes in the rows, samples in the columns, and y- a vector of the class labels for each sample. Same form as data object used by pamr.train.
nfold Number of cross-validation folds. Default is the smallest class size
folds A list with nfold components, each component a vector of indices of the samples in that fold. By default a (random) balanced cross-validation is used
...

{Any additional arguments that are to be passed to pamr.train}

Details

pamr.cv carries out cross-validation for a nearest shrunken centroid classifier.

Value

A list with components

threshold
errors The number of cross-validation errors for each threshold value
loglik The cross-validated multinomial log-likelihood value for each threshold value
size A vector of the number of genes that survived the thresholding, for each threshold value tried.
yhat A matrix of size n by nthreshold, containing the cross-validated class predictions for each threshold value, in each column
prob A matrix of size n by nthreshold, containing the cross-validated class probabilities for each threshold value, in each column
folds The cross-validation folds used
call The calling sequence used

Author(s)

Trevor Hastie,Robert Tibshirani, Balasubramanian Narasimhan, and Gilbert Chu

References

Examples

set.seed(120)
x <- matrix(rnorm(1000*20),ncol=20)
y <- sample(c(1:4),size=20,replace=TRUE)
mydata <- list(x=x,y=y)
mytrain <-   pamr.train(mydata)
mycv <- pamr.cv(mytrain,mydata)

[Package pamr version 1.12.1 Index]