PlotMixtureMultivariate | R Documentation |
Visualize data, centroids and response confidence intervals for a given Gaussian mixture model with PCA. Optionally, color the samples according to annotations labels.
PlotMixtureMultivariate(
x,
means,
sds,
ws,
labels = NULL,
title = NULL,
modes = NULL,
pca = FALSE,
qofz = NULL,
...
)
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. |
Used for its side-effects.
Leo Lahti leo.lahti@iki.fi
See citation('netresponse') for citation details.
#plotMixture(dat, means, sds, ws)
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