Gaussian Mixture Distribution

Fit, evaluate, and generate random samples from Gaussian mixture distribution

AGaussian mixture distributionis 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 objectgmdistributionby 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

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Create`gmdistribution`Object

`fitgmdist`	Fit Gaussian mixture model to data
`gmdistribution`	Create Gaussian mixture model

Work with`gmdistribution`Object

`cdf`	Cumulative distribution function for Gaussian mixture distribution
`cluster`	Construct clusters from Gaussian mixture distribution
`mahal`	Mahalanobis distance to Gaussian mixture component
`pdf`	Probability density function for Gaussian mixture distribution
`posterior`	Posterior probability of Gaussian mixture component
`random`	Random variate from Gaussian mixture distribution

Topics

Create Gaussian Mixture Model
创建一个已知或完全指定,高斯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 specifiedgmdistributionobject and therandomfunction.
Cluster Using Gaussian Mixture Model
Partition data into clusters with different sizes and correlation structures.

Gaussian Mixture Distribution

Functions

CreategmdistributionObject

Work withgmdistributionObject

Topics

Create`gmdistribution`Object

Work with`gmdistribution`Object