plot_DPMst: Plot of a Dirichlet process mixture of skew t-distribution...

In borishejblum/NPflow: Bayesian Nonparametrics for Automatic Gating of Flow-Cytometry Data

Plot of a Dirichlet process mixture of skew t-distribution partition

Description

Plot of a Dirichlet process mixture of skew t-distribution partition

Usage

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

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.
nice	logical flag changing the plot looks. Default is FALSE.

Author(s)

Boris Hejblum

borishejblum/NPflow documentation built on Feb. 2, 2024, 1:51 a.m.