A function that returns the shrunken gene (variable) names by RDA for a
particular (alpha, delta) combination.
Usage
genelist.rda(x, y, alpha, delta, prior=table(y)/length(y),
gnames=NULL, regularization="S")
Arguments
x
The training data set for which you want to obtain the
shrunken gene list. It must be a numerical matrix. The columns are sample
observations and the rows are variables.
y
The class labels for the columns of 'x'.
prior
A numerical vector that gives the prior proportion of each
class. By default, it is set to be the sample frequencies unless users
want to specify a different one.
alpha
A single regularization value for alpha. Users must supply
this option.
delta
A threshold value for delta. Users must supply this
option.
gnames
A character vector that specifies the names of the
variables of the training data set 'x'. By default, it is set to be
NULL and the function uses either the row names of 'x' (if it
exists) or the row index 1:nrow(x). Users can provide their
customized gene name list. However, the length of the name vector must be
the same as the number of rows of 'x'.
regularization
The type of regularization. It is either 'S' or
'R'. The default value is 'S'.
Value
A character vector of the names of the shrunken genes.
Details
genelist.rda will return a vector of names for those shrunken
genes by RDA for a particular (alpha, delta).
References
Guo, Y. et al. (2004) Regularized Discriminant Analysis and Its
Application in Microarrays, Technical Report, Department of Statistics,
Stanford University.