estimate_clusters {SANple}

Estimate observational and distributional clusters

Description

Given the MCMC output, estimate the observational and distributional partitions using salso::salso().

Usage

estimate_clusters(object, burnin = 0, ncores = 0)

Arguments

object

object of class SANmcmc (the result of a call to sample_fiSAN, sample_fiSAN_sparsemix, sample_fSAN, sample_fSAN_sparsemix, or sample_CAM).

burnin

the length of the burn-in to be discarded before estimating the clusters (default is 2/3 of the iterations).

ncores

the number of CPU cores to use, i.e., the number of simultaneous runs at any given time. A value of zero indicates to use all cores on the system.

Value

Object of class SANclusters. The object contains:

est_oc estimated partition at the observational level. It is an object of class salso.estimate.

est_dc estimated partition at the distributional level. It is an object of class salso.estimate.

clus_means cluster-specific sample means of the estimated partition.

clus_vars cluster-specific sample variances of the estimated partition.

See Also

salso::salso(), print.SANmcmc, plot.SANmcmc, print.SANclusters

Examples

set.seed(123)
y <- c(rnorm(40,0,0.3), rnorm(20,5,0.3))
g <- c(rep(1,30), rep(2, 30))
out <- sample_fiSAN(nrep = 500, burn = 200,
                     y = y, group = g, 
                    nclus_start = 2,
                    maxK = 20, maxL = 20,
                    beta = 1)
estimate_clusters(out)