ANOVA.estimators.COV: Variance components estimates in the presence of covariates

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

Description

This function estimates the genetic and the environmental variance components and the covariate effects using ANOVA and GLS approaches respectively.

Usage

ANOVA.estimators.COV(ntype, beta, X, Y, kin.miss)

Arguments

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.
beta	Ordinary least squares estimates of the covariate effects.
X	Model design matrix.
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	kinship matrix as a list with length the total number of families. Eeach object of the list represents a family kinship matrix.

Value

nnd.Mnt.e	Environmental variance-covariance matrix
nnd.Mnt.g	Genetic variance-covariance matrix
SSW	Subject-specific variance-covariance matrix
SSB	family-specific variance-covariance matrix

Author(s)

Karim Oualkacha

References

Oualkacha, K., Labbe, A., Ciampi, A., Roy, M.A. and Maziade, M., (2012). Principal components of heritability for high dimension quantitative traits and general pedigrees. Journal of Statistical Applications in Genetics and Molecular Biology, Volume 11. Issue 2, Article 4.

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