R: Plot of a Dirichlet process mixture of skew normal...

plot_DPMsn {NPflow} | R Documentation

## Plot of a Dirichlet process mixture of skew normal distribution partition

### Description

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(s)

Boris Hejblum

[Package NPflow version 0.13.3 Index]