dmbc (version 1.0.3)

update,dmbc_ic-method: Provide an update of a dmbc_ic class instance.

Description

Provide an update of a dmbc_ic class instance.

Usage

# S4 method for dmbc_ic
update(object, pmax = NULL, Gmax = NULL, ...)

Value

A dmbc_ic object.

Arguments

object

An object of class dmbc_ic.

pmax

A length-one numeric vector indicating the maximum number of dimensions of the latent space to consider.

Gmax

A length-one numeric vector indicating the maximum number of cluster to consider.

...

Further arguments to pass on (currently ignored).

Author

Sergio Venturini

References

Venturini, S., Piccarreta, R. (2021), "A Bayesian Approach for Model-Based Clustering of Several Binary Dissimilarity Matrices: the dmbc Package in R", Journal of Statistical Software, 100, 16, 1--35, <10.18637/jss.v100.i16>.

See Also

dmbc() for fitting a DMBC model.

dmbc_ic for a description of the elements included in the returned object.

Examples

if (FALSE) {
data(simdiss, package = "dmbc")

pmax <- 2
Gmax <- 2
prm.prop <- list(z = 1.5, alpha = .75)
burnin <- 2000
nsim <- 1000
seed <- 1809

set.seed(seed)

control <- list(burnin = burnin, nsim = nsim, z.prop = prm.prop[["z"]],
  alpha.prop = prm.prop[["alpha"]], random.start = TRUE, verbose = TRUE,
  thin = 10, store.burnin = TRUE)
sim.ic <- dmbc_IC(data = simdiss, pmax = pmax, Gmax = Gmax, control = control,
  est = "mean")

pmax <- pmax + 1
Gmax <- Gmax + 2
new.ic <- update(sim.ic, pmax = pmax, Gmax = Gmax)
new.ic

# plot the results
library(bayesplot)
library(ggplot2)
color_scheme_set("mix-yellow-blue")
p <- plot(new.ic, size = c(4, 1.5))
p + panel_bg(fill = "gray90", color = NA)
}