Return the estimated mixture proportions. Use get_estimated_pi to extract the estimates of the mixture proportions for different types of covariance matrix. This tells you which covariance matrices have most of the mass.

Return the estimated mixture proportions. Use get_estimated_pi to extract the estimates of the mixture proportions for different types of covariance matrix. This tells you which covariance matrices have most of the mass.

get_estimated_pi(m, dimension = c("cov", "grid", "all"))

Arguments

m

the mash result

dimension

indicates whether you want the mixture proportions for the covariances, grid, or all

Value

a named vector containing the estimated mixture proportions.

Details

If the fit was done with usepointmass=TRUE then the first element of the returned vector will correspond to the null, and the remaining elements to the non-null covariance matrices. Suppose the fit was done with $K$ covariances and a grid of length $L$. If dimension=cov then the returned vector will be of length $K$ (or $K+1$ if usepointmass=TRUE). If dimension=grid then the returned vector will be of length $L$ (or $L+1$). If dimension=all then the returned vector will be of length $LK$ (or $LK+1$). The names of the vector will be informative for which combination each element corresponds to.