get.cp: Uses bootstrap sampling over a vector of LD LASSO constraint...

In ldlasso: LD LASSO Regression for SNP Association Study

Description

The vector of cp estimates is used to identify the cp-optimal solution.

Usage

get.cp(s2low, s2high, s2.vec.length, block.obj, Xa = NA, Y = NA, s1, r2.cut, block.cood, B = 20)

Arguments

s2low	The lower limit for the s2 vector.
s2high	The upper limit for the s2 vector.
s2.vec.length	The number of exponentially spaced values in the s2 vector.
block.obj	An object of class gwaa.data from GenABEL.
Xa	If block.obj is NA then a genotype matrix must be provided. Xa is a matrix of genotype values codes as 0, 1 or 2 for homozygous major, heterozygous, or homozygous minor, respectively.
Y	If block.obj is NA then a phenotype vector Y must be provided. Y is a vector of diagnoses, where 0 is non-diseased and 1 is diseased.
s1	The LASSO parameter
r2.cut	Only SNP pairs with correlation greater than r2.cut are bounded by the LD LASSO constraint.
block.cood	A vector of length p+1, where p is the number of SNPs. block.cood is an indicator vector that indicates block boundaries at all p+1 SNP bounded intervals. Use find.bounds to create this vector.
B	Number of bootstrap samples

Value

s2.vec	A vector of s2 values
cp.vec	A vector of cp estimates
beta0.mat	A matrix of LD LASSO estimates
s1	The LASSO parameter

Author(s)

Samuel G. Younkin

See Also

ld_lasso_method

ldlasso documentation built on May 30, 2017, 3:05 a.m.