calcpca: Do dimensional reduction using pca.

In ikwak2/funqtl: QTL Mapping for Function-Valued Traits

Do dimensional reduction using pca.

Description

Do dimensional reduction using pca.

Usage

calcpca(cross, pheno.cols, n.max = 5, criteria = 0.9, nn = 0)

Arguments

cross	An object of class "cross". See the read.cross for details.
pheno.cols	Columns in the phenotype matrix to be used as the phenotype.
n.max	The number of maximum reduced dimension.
criteria	how much of variance explained.
nn	The number of exact reduced dimension

Value

It gives a matrix that each column have principal components.

Author(s)

Il-Youp Kwak, <email: [e-mail]>

See Also

scanoneM

Examples

data(exd)
exd <- calc.genoprob(exd, step=2)
Y <- calcpca(exd, criteria=0.9)
out1 <- scanoneM(exd, Y, method = "hk")

ikwak2/funqtl documentation built on April 20, 2022, 3:58 a.m.