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.