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)
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. |
Since this function uses multivariate normal model to generate populations, only covariance matrices should be used.
returns a vector with the R2 for all populations
Diogo Melo Guilherme Garcia
r2.dist <- MonteCarloR2(RandomMatrix(10, 1, 1, 10), 30) quantile(r2.dist)
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