`obj = gmdistribution(mu,sigma,p)`

`obj = gmdistribution(mu,sigma,p)`

constructs
an object `obj`

of the `gmdistribution`

class defining a Gaussian
mixture distribution.

`mu`

is a *k*-by-*d* matrix
specifying the *d*-dimensional mean of each of the *k* components.

`sigma`

specifies the covariance of each component.
The size of `sigma`

is:

*d*-by-*d*-by-*k*if there are no restrictions on the form of the covariance. In this case,`sigma(:,:,I)`

is the covariance of component`I`

.1-by-

*d*-by-*k*if the covariance matrices are restricted to be diagonal, but not restricted to be same across components. In this case,`sigma(:,:,I)`

contains the diagonal elements of the covariance of component I.*d*-by-*d*matrix if the covariance matrices are restricted to be the same across components, but not restricted to be diagonal. In this case,`sigma`

is the pooled estimate of covariance.1-by-

*d*if the covariance matrices are restricted to be diagonal and the same across components. In this case,`sigma`

contains the diagonal elements of the pooled estimate of covariance.

`p`

is an optional 1-by-*k* vector
specifying the mixing proportions of each component. If `p`

does
not sum to `1`

, `gmdistribution`

normalizes
it. The default is equal proportions.

[1] McLachlan, G., and D. Peel. *Finite
Mixture Models*. Hoboken, NJ: John Wiley & Sons, Inc.,
2000.

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