Last chance! 50% off unlimited learning
Sale ends in
dmbc_get_configuration()
is an extractor function for extracting the
latent configuration estimates of a fitted DMBC model.
dmbc_get_configuration(res, chain = 1, est = "mean", labels = character(0))
An object of class dmbc_fit_list
.
A length-one numeric vector indicating the MCMC chain number to use.
A length-one character vector indicating the estimate type to use.
An optional character vector with the object labels.
A dmbc_config
object.
Venturini, S., Piccarreta, R. (2019), "A Bayesian Approach for Model-Based
Clustering of Several Binary Dissimilarity Matrices: the dmbc
Package in R
", Technical report.
dmbc_data
for a description of the data format.
dmbc_fit_list
for a description of the elements
included in the returned object.
# NOT RUN {
data(simdiss, package = "dmbc")
G <- 3
p <- 2
prm.prop <- list(z = 1.5, alpha = .75)
burnin <- 2000
nsim <- 1000
seed <- 2301
set.seed(seed)
control <- list(burnin = burnin, nsim = nsim, z.prop = prm.prop[["z"]],
alpha.prop = prm.prop[["alpha"]], random.start = TRUE, verbose = TRUE,
nchains = 2, thin = 10, store.burnin = TRUE, threads = 2,
parallel = "snow")
sim.dmbc <- dmbc(simdiss, p, G, control)
z <- dmbc_get_configuration(sim.dmbc, chain = 1, est = "mean")
summary(z)
library(bayesplot)
library(ggplot2)
color_scheme_set("mix-pink-blue")
graph <- plot(z, size = 2, size_lbl = 3)
graph + panel_bg(fill = "gray90", color = NA)
# }
Run the code above in your browser using DataLab