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ERIC Number: ED395962
Record Type: RIE
Publication Date: 1989-Apr
Pages: 20
Abstractor: N/A
Reference Count: N/A
Classes of Multivariate Exponential and Multivariate Geometric Distributions Derived from Markov Processes. Program Statistics Research Technical Report No. 89-87.
Longford, Nicholas T.
A class of multivariate exponential distributions is defined as the distributions of occupancy times in upwards skip-free Markov processes in continuous time. These distributions are infinitely divisible, and the multivariate gamma class defined by convolutions and fractions is a substantial generalization of the class defined by N. L. Johnson and S. Kotz (1972). Parallel classes of multivariate geometric and multivariate negative binomial distributions are constructed from occupancy times in "instant" upwards skip-free Markov chains. Maximum likelihood estimation and time series applications are discussed. An appendix demonstrates the density of trivariate exponential distribution. (Contains 17 references.) (Author/SLD)
Publication Type: Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: Educational Testing Service, Princeton, NJ.
Identifiers: Time Series Analysis