evolqg (version 0.2-2)

RSProjection: Random Skewers projection

Description

Not tested! Uses MCMC Bayeisian posterior samples of a set of covariance matrices to identify directions of the morphospace in which these matrices differ in their amount of genetic variance.

Usage

RSProjection(cov.matrix.array, p = 0.95, num.vectors = 1000)

Arguments

cov.matrix.array

Array with dimentions traits x traits x populations x MCMCsamples

p

significance treashhold for comparison of variation in each random direction

num.vectors

number of random vectors

Value

• projection of all matrices in all random vectors

  set of random vectors and confidence intervals for the projections

  eigen decomposition of the random vectors in directions with significant differences of variations #@export

References

Aguirre, J. D., E. Hine, K. McGuigan, and M. W. Blows. "Comparing G: multivariate analysis of genetic variation in multiple populations." Heredity 112, no. 1 (2014): 21-29.

Examples

#random set of covariance matrices 
cov.matrices = aperm(aaply(1:15, 1, function(x) 
                     laply(RandomMatrix(10, 100, 
                           variance = runif(10, 1, 10)), 
                           identity)), 
                     c(3, 4, 1, 2))
#rs_proj = evolqg:::RSProjection(cov.matrices, p = 0.8)  
#plot(rs.proj, cov.matrices)