PlotMixtureMultivariate: PlotMixtureMultivariate

View source: R/plot-methods.R

PlotMixtureMultivariateR Documentation

PlotMixtureMultivariate

Description

Visualize data, centroids and response confidence intervals for a given Gaussian mixture model with PCA. Optionally, color the samples according to annotations labels.

Usage

PlotMixtureMultivariate(
  x,
  means,
  sds,
  ws,
  labels = NULL,
  title = NULL,
  modes = NULL,
  pca = FALSE,
  qofz = NULL,
  ...
)

Arguments

x

data matrix (samples x features)

means

mode centroids (modes x features)

sds

mode standard deviations, assuming diagonal covariance matrices (modes x features, each row giving the sqrt of covariance diagonal for the corresponding mode)

ws

weight for each mode

labels

Optional: sample class labels to be indicated in colors.

title

title

modes

Optional: provide sample modes for visualization already in the input

pca

The data is projected on PCA plane by default (pca = TRUE). By setting this off (pca = FALSE) it is possible to visualize two-dimensional data in the original domain.

qofz

Sample-response probabilistic assignments matrix (samples x responses)

...

Further arguments for plot function.

Value

Used for its side-effects.

Author(s)

Leo Lahti leo.lahti@iki.fi

References

See citation('netresponse') for citation details.

Examples

#plotMixture(dat, means, sds, ws)

antagomir/netresponse documentation built on March 30, 2023, 7:24 a.m.