Plot of a Dirichlet process mixture of skew normal distribution partition

Plot of a Dirichlet process mixture of skew normal distribution partition

Usage

plot_DPMsn(
  z,
  c,
  i = "",
  alpha = "?",
  U_SS,
  dims2plot = 1:nrow(z),
  ellipses = ifelse(length(dims2plot) < 3, TRUE, FALSE),
  gg.add = list(theme()),
  nbsim_dens = 1000
)

Arguments

z

data matrix d x n with d dimensions in rows and n observations in columns.

c

allocation vector of length n indicating which observation belongs to which clusters.

i

current MCMC iteration number.

alpha

current value of the DP concentration parameter.

U_SS

a list containing "xi", "psi", "S", and "df".

dims2plot

index vector, subset of 1:d indicating which dimensions should be drawn. Default is all of them.

ellipses

a logical flag indicating whether ellipses should be drawn around clusters. Default is TRUE if only 2 dimensions are plotted, FALSE otherwise.

gg.add

A list of instructions to add to the ggplot2 instruction (see gg-add). Default is list(theme()), which adds nothing to the plot.

nbsim_dens

number of simulated points used for computing clusters density contours in 2D plots. Default is 1000 points.

Author

Boris Hejblum