computes matrix of likelihoods for each of J rows of Bhat for each of P prior covariances; special case when standard errors and variances are all same across j.
This is an internal (non-exported) function. This help page provides additional documentation mainly intended for developers and expert users.
calc_lik_matrix_common_cov(data, Ulist, log = FALSE)J x P vector of multivariate normal likelihoods, p(bhat | Ulist[p], V), where V is same for each bhat
a mash data object, eg as created by mash_set_data
list of prior covariance matrices
if true computes log-likelihood
Compared with calc_lik_matrix this function
exploits fact that observations are iid in this case, so the
inverse covariance matrices only need to be done once, reducing
computation to R^3 + JR^2 instead of JR^3