compute_mean_variance.simple
computes the quantities needed to compute
mean and variance matrix with parameters params_old.
compute_mean_variance.simple(phylo, times_shared, distances_phylo, process = c("BM", "OU", "rBM", "scOU"), params_old, masque_data = c(rep(TRUE, attr(params_old, "p_dim") * length(phylo$tip.label)), rep(FALSE, attr(params_old, "p_dim") * phylo$Nnode)), sim = NULL, U_tree = NULL, ...)
compute_times_ca
compute_dist_phy
simulate
with the appropriate
parametersSigma matrix of variance covariance, result of function
compute_variance_covariance
#@return Sigma_YY_inv inverse of vairance matrix of the dataSigma_YY_chol_inv invert of cholesky matrix of Sigma_YY:
(Sigma_YY)^(-1) = tcrossprod(Sigma_YY_chol_inv)
compute_E.simple
and
compute_log_likelihood.simple
.