index.md

VarianceComponentModels.jl

Utilities for fitting and testing variance component models

VarianceComponentModels.jl implements computation routines for fitting and testing variance component model of form

$\text{vec}(Y) \sim \text{Nomral}(X B, \Sigma_1 \otimes V_1 + \cdots + \Sigma_m \otimes V_m),$

where $\otimes$ is the Kronecker product.

In this model, data is represented by

• Y: n x d response matrix
• X: n x p covariate matrix
• V=(V1,...,Vm): a tuple m n x n covariance matrices

and parameters are

• B: p x d mean parameter matrix
• Σ=(Σ1,...,Σm): a tuple of m d x d variance components

Package Features

• Maximum likelihood estimation (MLE) and restricted maximum likelihood estimation (REML) of mean parameters B and variance component parameters Σ
• Allow constrains in the mean parameters B
• Choice of optimization algorithms: Fisher scoring and minorization-maximization algorithm
• Heritability Analysis in genetics

Installation

Use the Julia package manager to install VarianceComponentModels.jl.

Pkg.clone("https://github.com/OpenMendel/VarianceComponentModels.jl.git")

This package supports Julia 0.6.

Manual Outline

Pages = [
    "man/mle_reml.md",
    "man/heritability.md",
]
Depth = 2