PlotMixtureMultivariate {netresponse} | R 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)

[Package netresponse version 1.52.0 Index]