Pdmclass Function to Classify Microarray Data Using Penalized Discriminant Methods

Description This function is used to classify microarray data. Since the underlying model fit is based on penalized discriminant methods, there is no need for a pre-filtering step to reduce the number of genes. Usage pdmClass(formula , method = c("pls", "pcr", "ridge"), keep.fitted = Arguments formula A symbolic description of the model to be fit. Details given below. method One of "pls", "pcr", "ridge", corresponding to partial least squares, principal components regression and ridge regression. Additional parameters to pass to method or fda. See fda for more information. Details The formula interface is identical to all other formula calls in R, namely Y ~ X, where Y is a numeric vector of class assignments and X is a matrix or data.frame containing the gene expression values. Note that unlike most microarray analyses, in this instance the columns of X are genes and rows are samples, so most calls will require something similar to Y ~ t(X). Value an object of class "fda". Use predict to extract discriminant variables, posterior probabilities or predicted class memberships. Other extractor functions are coef, and plot.