CV.lambda.Wang: Cross validation techniques for regularisation parameter

In KarimOualkacha/PCH4Pedigees: Principal Components of Heritability for High Dimension Quantitative Traits and General Pedigrees

Description

This function use cross validation techniques to calculate the regularisation parameter, Wang et al. (2007).

Usage

CV.lambda.Wang(lambda1, lambda2, ntype, N.part, u, Y, kin.miss)

Arguments

lambda1	Real number.
lambda2	Real number.
ntype	Vector of integers. Its length equals to the total number of families used in the pedigree file. The ntype's entries are the total number of subjects within each family.
N.part	Integer indicates the number of times that the data will be splited to training data and validation data.
u	Matrix of integers used to separate randomly the families to two groups of families: training and validation data.
Y	List of matrices obtained from the function ANOVA.data(). Its length equals to the number of families used in the study. Each matrix of this list represents one family of the pedigree file (i. e. each list entry has subjects of a same family as rows and their corresponding traits as columns).
kin.miss	List of matrices. Its length equals to the total number of families. The list entries represent the family kinship matrices.

Value

Cross validation heritability, see Wang et al. (2007).

Author(s)

Karim Oualkacha

References

Wang Y, Fang Y, Jin M (2007). A ridge penalized principal-components approach based on heritability for high-dimensional data. Hum Hered, 64, 182-191.

KarimOualkacha/PCH4Pedigees documentation built on May 20, 2019, 8:30 a.m.