solveRRBLUP_EM3

Solves a univariate mixed model of form \(y=X\beta+M_1u_1+M_2u_2+M_3u_3+e\) using
the Expectation-Maximization algorithm.

The successor to the 'AlphaSim' software for breeding program
simulation [Faux et al. (2016) <doi:10.3835/plantgenome2016.02.0013>].
Used for stochastic simulations of breeding programs to the level of DNA
sequence for every individual. Contained is a wide range of functions for
modeling common tasks in a breeding program, such as selection and crossing.
These functions allow for constructing simulations of highly complex plant and
animal breeding programs via scripting in the R software environment. Such
simulations can be used to evaluate overall breeding program performance and
conduct research into breeding program design, such as implementation of
genomic selection. Included is the 'Markovian Coalescent Simulator' ('MaCS')
for fast simulation of biallelic sequences according to a population
demographic history [Chen et al. (2009) <doi:10.1101/gr.083634.108>].

Chris Gaynor

AlphaSimR

Breeding Program Simulations

Gregor Gorjanc

John Hickey

Daniel Money

David Wilson

Thiago Oliveira

Audrey Martin

Philip Greenspoon

solveRRBLUP_EM3 function

<dl><dt>Y</dt>
<dd>a matrix with n rows and 1 column</dd>
<dt>X</dt>
<dd>a matrix with n rows and x columns</dd>
<dt>M1</dt>
<dd>a matrix with n rows and m1 columns</dd>
<dt>M2</dt>
<dd>a matrix with n rows and m2 columns</dd>
<dt>M3</dt>
<dd>a matrix with n rows and m3 columns</dd>
<dt>Vu1</dt>
<dd>initial guess for variance of the first marker effects</dd>
<dt>Vu2</dt>
<dd>initial guess for variance of the second marker effects</dd>
<dt>Vu3</dt>
<dd>initial guess for variance of the second marker effects</dd>
<dt>Ve</dt>
<dd>initial guess for error variance</dd>
<dt>tol</dt>
<dd>tolerance for declaring convergence</dd>
<dt>maxIter</dt>
<dd>maximum iteration for attempting convergence</dd>
<dt>useEM</dt>
<dd>should EM algorithm be used. If false, no estimation of
variance components is performed. The initial values are treated as true.</dd></dl>

Arguments

Solve RR-BLUP with EM and 3 random effects — solveRRBLUP_EM3

<dl>

<dt>Y</dt>
<dd>a matrix with n rows and 1 column</dd>


<dt>X</dt>
<dd>a matrix with n rows and x columns</dd>


<dt>M1</dt>
<dd>a matrix with n rows and m1 columns</dd>


<dt>M2</dt>
<dd>a matrix with n rows and m2 columns</dd>


<dt>M3</dt>
<dd>a matrix with n rows and m3 columns</dd>


<dt>Vu1</dt>
<dd>initial guess for variance of the first marker effects</dd>


<dt>Vu2</dt>
<dd>initial guess for variance of the second marker effects</dd>


<dt>Vu3</dt>
<dd>initial guess for variance of the second marker effects</dd>


<dt>Ve</dt>
<dd>initial guess for error variance</dd>


<dt>tol</dt>
<dd>tolerance for declaring convergence</dd>


<dt>maxIter</dt>
<dd>maximum iteration for attempting convergence</dd>


<dt>useEM</dt>
<dd>should EM algorithm be used. If false, no estimation of
variance components is performed. The initial values are treated as true.</dd>

</dl>

solveRRBLUP_EM3: Solve RR-BLUP with EM and 3 random effects

Description

Usage

Arguments