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Calculate Vg and Ve from d-variate phenotype and kinship
calc_covs( pheno, kinship, X1pre = rep(1, nrow(kinship)), max_iter = 1e+06, max_prec = 1/1e+08, covariates = NULL )
n by d matrix of phenotypes
a kinship matrix, n by n
n by c design matrix. c = 1 to ignore genotypes
maximum number of EM iterations
maximum precision for stepwise increments in EM algorithm
a n by n.cov matrix of numeric covariates
a list with 2 named components, Vg and Ve. Each is a d by d covariance matrix.
# NOT RUN { calc_covs(pheno = matrix(data = rnorm(100), nrow = 50, ncol = 2), kinship = diag(50)) # }
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