msecalcmult {LMGene}R Documentation

MSE calculation function

Description

Computes the mean square error and gradient for the global ANOVA.

Usage

msecalcmult(eS, lam, alpha, lowessnorm=FALSE, R, grads=TRUE)

Arguments

eS Array data. must be an ExpressionSet object.
lam A parameter for glog transformation.
alpha A parameter for glog transformation.
lowessnorm TRUE, if lowess method is going to be used.
R The residual matrix, i.e., identity minus the hat matrix.
grads If TRUE, return gradient as well as error. Not used with some kinds of optimization.

Details

The argument eS must be an ExpressionSet object from the Biobase package. If you have a data in a matrix and information about the considered factors, then you can use neweS to convert the data into an ExpressionSet object. Please see neweS in more detail.

Value

msev A vector which contains MSE and gradient of two parameters.

Author(s)

David Rocke and Geun-Cheol Lee

References

B. Durbin and D.M. Rocke, (2003) Estimation of Transformation Parameters for Microarray Data, Bioinformatics, 19, 1360-1367.

http://www.idav.ucdavis.edu/~dmrocke/

See Also

jggrad2, tranest2

Examples

#library
library(Biobase)
library(LMGene)

#data
data(sample.eS)

lmod <- GetLMObj(sample.eS)
X <- lmod$x
U <- svd(X)$u
H <- crossprod(t(U), t(U))
n <- dim(H)[1]
R <- diag(rep(1,n)) - H

msecalc(sample.eS,500,50, FALSE, R)

[Package LMGene version 1.12.0 Index]