dmbc_fit()
is the main function that estimates a DMBC model.
dmbc_fit(D, p, G, family, control, prior, start)
A list whose elements are the dissimilarity matrices corresponding
to the judgments expressed by the S subjects/raters. These matrices
must be defined as a dist
object.
A length-one numeric vector indicating the number of dimensions of the latent space.
A length-one numeric vector indicating the number of cluster to partition the S subjects.
A length-one character vector representing the type of data to analyze. Currently, it accepts only the 'binomial' value, but future developments will include the possibility to analyze continuous, multinomial and count data.
A list of control parameters that affect the sampling
but do not affect the posterior distribution See
dmbc_control()
for more details.
A list containing the prior hyperparameters. See
dmbc_prior()
for more details.
A named list of starting values for the MCMC algorithm (see
dmbc_init
).
A dmbc_fit_list
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 <- 20000
nsim <- 10000
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)
summary(sim.dmbc, include.burnin = FALSE)
library(bayesplot)
library(ggplot2)
color_scheme_set("teal")
plot(sim.dmbc, what = "trace", regex_pars = "eta")
z <- dmbc_get_configuration(sim.dmbc, chain = 1, est = "mean",
labels = 1:16)
summary(z)
color_scheme_set("mix-pink-blue")
graph <- plot(z, size = 2, size_lbl = 3)
graph + panel_bg(fill = "gray90", color = NA)
# }
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