Gaussian Mixture Distribution
A Gaussian mixture distribution is a multivariate
distribution that consists of multivariate Gaussian distribution components.
Each component is defined by its mean and covariance, and the mixture is
defined by a vector of mixing proportions. Create a distribution object
gmdistribution by fitting a model
to data (fitgmdist) or by specifying
parameter values (gmdistribution). Then, use object
functions to perform cluster analysis (cluster, posterior, mahal), evaluate the
distribution (cdf, pdf), and generate random
variates (random).
Functions
Topics
- Create Gaussian Mixture Model
Create a known, or fully specified, Gaussian mixture model (GMM) object.
- Fit Gaussian Mixture Model to Data
Simulate data from a multivariate normal distribution, and then fit a Gaussian mixture model (GMM) to the data.
- Simulate Data from Gaussian Mixture Model
Simulate data from a Gaussian mixture model (GMM) using a fully specified
gmdistributionobject and therandomfunction. - Cluster Using Gaussian Mixture Model
Partition data into clusters with different sizes and correlation structures.
