Compute a list of covariance matrices corresponding to the "Unassociated", "Directly associated" and "Indirectly associated" models
cov_udi(data, model = udi_model_matrix(n_conditions(data)))
a mash data object, eg as created by
a model matrix with R columns, where R is the number of conditions in the data; each row should be a vector of length R with elements "U","D" and "I" indicating whether each effect is Unassociated, Directly associated or Indirectly associated
If model is specified then this returns the covariance matrices for those models. The default creates all possible models. For a desription of the "Unassociated", "Directly associated" and "Indirectly associated" models see Stephens M (2013), A unified framework for Association Analysis with Multiple Related Phenotypes, PloS ONE.
a named list of covariance matrices
data = mash_set_data(Bhat = cbind(c(1,2),c(3,4)), Shat = cbind(c(1,1),c(1,1))) cov_udi(data) cov_udi(data,c('I','D'))
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