MonteCarloR2 function

R2 confidence intervals by parametric sampling

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.

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.

Returns

returns a vector with the R2 for all populations

Details

Since this function uses multivariate normal model to generate populations, only covariance matrices should be used.

Examples

r2.dist <- MonteCarloR2(RandomMatrix(10, 1, 1, 10), 30)
quantile(r2.dist)

See Also

BootstrapRep, AlphaRep

Author(s)

Diogo Melo Guilherme Garcia