Classes of Multivariate Exponential and Multivariate Geometric Distributions Derived from Markov Processes. Program Statistics Research Technical Report No. 89-87.

Autor/in	Longford, Nicholas T.
Institution	Educational Testing Service, Princeton, NJ.
Titel	Classes of Multivariate Exponential and Multivariate Geometric Distributions Derived from Markov Processes. Program Statistics Research Technical Report No. 89-87.
Quelle	(1989), (20 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Exponents (Mathematics); Markov Processes; Maximum Likelihood Statistics; Multivariate Analysis; Statistical Distributions + Suchen Sie Ihr Suchwort? Markowscher Prozess; Multivariate Analyse; Wahrscheinlichkeitsverteilung
Abstract	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)
Erfasst von	ERIC (Education Resources Information Center), Washington, DC