A function that returns the shrunken gene (variable) names by RDA for a particular (alpha, delta) combination.
genelist.rda(x, y, alpha, delta, prior=table(y)/length(y),
gnames=NULL, regularization="S")
A character vector of the names of the shrunken genes.
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.
The class labels for the columns of 'x'.
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.
A single regularization value for alpha. Users must supply this option.
A threshold value for delta. Users must supply this option.
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'.
The type of regularization. It is either 'S' or 'R'. The default value is 'S'.
Yaqian Guo, Trevor Hastie and Robert Tibshirani
genelist.rda
will return a vector of names for those shrunken
genes by RDA for a particular (alpha, delta).
Y. Guo, T. Hastie, R. Tibshirani, (2006). Regularized linear discriminant analysis and its application in microarrays, Biostatistics 8 pp. 86--100. tools:::Rd_expr_doi("10.1093/biostatistics/kxj035").
data(colon)
colon.x <- t(colon.x)
genenames <- genelist.rda(colon.x, colon.y, alpha=0.1, delta=0.3)
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