gm = gmdistribution(mu, Sigma)
gm = gmdistribution(mu, Sigma, p)
y = pdf(gm, X)
P = posterior(gm, X)
idx = cluster(gm, X)
R = random(gm, n)
gmdistribution creates a Gaussian mixture model object from component means, covariance matrices, and optional component proportions.
The object supports density evaluation with pdf, posterior probabilities with posterior, maximum-posterior assignment with cluster, and random sampling with random.
gm = gmdistribution([0; 10], cat(3, 1, 4), [0.25 0.75]);
y = pdf(gm, [0; 10; 5])
P = posterior(gm, [0; 10; 5])| Version | Description |
|---|---|
| 2.0.0 | initial version |