MDR.stage.forward: MDR based forward selection method

In CateSelection: Categorical Variable Selection Methods

Description

MDR based forward selection method for association mapping

Usage

MDR.stage.forward(x, y, order = NULL, s1.rsquared = NULL, s1.pvalue = NULL, 
s2.rsquared = NULL, s2.pvalue = NULL, max.step = NULL, trace = NULL, ...)

Arguments

x	A matrix of genotypic data/genetic markers (predictor variables), where the rows are the samples and the columns are the predictors.
y	A numeric vector of phenotypic data (response variable).
order	The order of interaction. Default is 2.
s1.rsquared	Cutoff value for coefficient of determination in the first stage. Default is 0.02.
s1.pvalue	Cutoff value for p-value in the first stage. Default is 0.01.
s2.rsquared	Cutoff value for coefficient of determination in the second stage. Default is 0.02.
s2.pvalue	Cutoff value for p-value in the second stage. Default is 0.01.
max.step	The maximum selection step. Default is 100.
trace	Show computations? Default FALSE.
...	Other arguments for future methods.

Value

It returns a matrix with the index of selected interactive predictors, and the corresponding adjusted coefficient of determination for each step.

References

Yi Xu, Jixiang Wu, Detecting epistatic effects among SNP markers associated with three barley traits by a MDR based forward selection method (unpublished).

Examples

data(data1)
y <- data1[,1]
x <- data1[,-1]
res <- MDR.stage.forward(x,y,order=2)
res

CateSelection documentation built on May 1, 2019, 10:11 p.m.