MonteCarloR2 {evolqg} | R Documentation |
R2 confidence intervals by parametric sampling
Description
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.
Usage
MonteCarloR2(cov.matrix, sample.size, iterations = 1000, parallel = FALSE)
Arguments
cov.matrix |
Covariance matrix. |
sample.size |
Size of the random populations |
iterations |
Number of random populations |
parallel |
if TRUE computations are done in parallel. Some foreach backend must be registered, like doParallel or doMC. |
Details
Since this function uses multivariate normal model to generate populations, only covariance matrices should be used.
Value
returns a vector with the R2 for all populations
Author(s)
Diogo Melo Guilherme Garcia
See Also
Examples
r2.dist <- MonteCarloR2(RandomMatrix(10, 1, 1, 10), 30)
quantile(r2.dist)
[Package evolqg version 0.3-4 Index]