PScv {GolubRR}R Documentation

Compute the Weighted Voting Statistics Using Cross Validation.

Description

The weighted voting statistics described in Golub et al are computed using leave one out cross-validation.

Usage

PScv(eset, cov)

Arguments

eset An object of class exprSet that contains the expression data to be analysed.
cov A vector indicating which of two classes each sample belongs to.

Details

Each sample is left out in turn and an object of class vstruct is computed using the remaining samples. This object is then used, together with the left out sample to obtain the votes and PS for the left out sample. The function returns a list with one entry for each sample.

Value

A list with one entry for each sample. The entries are the output of dovote and are described there.

Author(s)

R. Gentleman

References

Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring, Science, 531-537, 1999, T. R. Golub and D. K. Slonim and P. Tamayo and C. Huard and M. Gaasenbeek and J. P. Mesirov and H. Coller and M.L. Loh and J. R. Downing and M. A. Caligiuri and C. D. Bloomfield and E. S. Lander

See Also

dovote

Examples

   library(golubEsets)
   ans <- PScv(golubTrain[1:20,], golubTrain$ALL)

[Package GolubRR version 1.3.1 Index]