Package smile.stat.distribution

Interface MultivariateExponentialFamily

All Known Implementing Classes:
MultivariateGaussianDistribution
public interface MultivariateExponentialFamily
The purpose of this interface is mainly to define the method M that is the Maximization step in the EM algorithm. Note that distributions of exponential family has the close-form solutions in the EM algorithm. With this interface, we may allow the mixture contains distributions of different form as long as it is from exponential family.
See Also:

  • Method Summary

    Modifier and Type
    Method
    Description
    MultivariateMixture.Component
    M(double[][] x, double[] posteriori)
    The M step in the EM algorithm, which depends on the specific distribution.

  • Method Details

    • M

      MultivariateMixture.Component M(double[][] x, double[] posteriori)
      The M step in the EM algorithm, which depends on the specific distribution.
      Parameters:
      x - the input data for estimation
      posteriori - the posteriori probability.
      Returns:
      the (unnormalized) weight of this distribution in the mixture.