MonteCarloR2

Using a multivariate normal model, random populations are generated
using the suplied covariance matrix. R2 is calculated on all the
random population, provinding a distribution based on the original matrix.

Repeatability

montecarlo

parametricsampling

Provides functions for covariance matrix comparisons, estimation of repeatabilities in measurements and matrices, and general evolutionary quantitative genetics tools. Melo D, Garcia G, Hubbe A, Assis A P, Marroig G. (2016) <doi:10.12688/f1000research.7082.3>.

Diogo Melo

evolqg

Evolutionary Quantitative Genetics

Ana Paula Assis

Edgar Zanella

Fabio Andrade Machado

Guilherme Garcia

Alex Hubbe

Gabriel Marroig

MonteCarloR2 function

<dl><dt>cov.matrix</dt>
<dd>Covariance matrix.</dd>
<dt>sample.size</dt>
<dd>Size of the random populations</dd>
<dt>iterations</dt>
<dd>Number of random populations</dd>
<dt>parallel</dt>
<dd>if TRUE computations are done in parallel. Some foreach backend must be registered, like doParallel or doMC.</dd></dl>

Arguments

Author

R2 confidence intervals by parametric sampling — MonteCarloR2

<dl>

<dt>cov.matrix</dt>
<dd>Covariance matrix.</dd>


<dt>sample.size</dt>
<dd>Size of the random populations</dd>


<dt>iterations</dt>
<dd>Number of random populations</dd>


<dt>parallel</dt>
<dd>if TRUE computations are done in parallel. Some foreach backend must be registered, like doParallel or doMC.</dd>

</dl>

R2 confidence intervals by parametric sampling

MonteCarloR2: R2 confidence intervals by parametric sampling

Description

Usage

Value

Arguments

Author

Details

See Also

Examples