fhmm_fit: finite heirarchical mixture model - C++ estimation engine
In apeterson91/fhmm:

finite heirarchical mixture model - C++ estimation engine

1 2	fhmm_fit(r, n_j, d, L, K, J, mu_0, kappa_0, nu_0, sigma_0, iter_max, warm_up, thin, seed, chain, num_posterior_samples)

`r`	vector of distances associatd with different BEFs
`n_j`	matrix of integers denoting the start and length of each observations associated BEF distances
`d`	a 1D grid of positive real values over which the differing intensities are evaluated
`L`	number of cluster mixture components
`K`	number of function components
`J`	number of rows in r matrix; number of groups
`mu_0`	prior mean for mean parameter
`kappa_0`	prior variance parameter for mean normal prior
`nu_0`	prior degrees of freedom for variance Inv Chisq prior
`sigma_0`	prior scale for variance Inv-Chisq distribtuion
`iter_max`	number of total iterations to run the sampler for
`warm_up`	number of iterations to discard as burn-in or warm_up
`thin`	number of iterations to thin posterior sample draws by
`seed`	seed with which to initialize random number generator
`chain`	used for labeling
`num_posterior_samples`	number of posterior samples kept after thinning