Stochastic Process Mixture

A Stochastic Process Mixture is a process mixture composed of two or more stochastic processes.

• Context:
  • It can be represented by a Stochastic Mixture Function.
• Example(s):
  • a Gaussian Process Mixture.
  • a Poisson Process Mixture.
  • a Dirichlet Process Mixture.
• See: Mixture Model, Blind Source Separation.

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References

2011

• http://www.vosesoftware.com/ModelRiskHelp/index.htm#Probability_theory_and_statistics/Stochastic_processes/Mixture_processes.htm
  • Sometimes a stochastic process can be a combination of two or more separate processes. For example, car accidents at some particular place and time could be considered to be a Poisson variable, but the mean number of accidents per unit time l may be a variable too. Perhaps the accident rate is dependent on the weather. Then the number of accidents in a particular period will be a mixture of a Poisson distribution and a distribution for l.

2004

• (Lartillot & Philippe, 2004) ⇒ Nicolas Lartillot, and Hervé Philippe. (2004). “A Bayesian Mixture Model for Across-site Heterogeneities in the Amino-acid Replacement Process." Molecular biology and evolution 21, no. 6

2000

• (Neal, 2000) ⇒ Radford M. Neal. (2000). “Markov Chain Sampling Methods for Dirichlet Process Mixture Models." Journal of computational and graphical statistics 9, no. 2

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