𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Moment Properties of the Multivariate Dirichlet Distributions

✍ Scribed by Rameshwar D. Gupta; Donald St.P. Richards


Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
169 KB
Volume
82
Category
Article
ISSN
0047-259X

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


An Expectation Formula for the Multivari
✍ GΓ©rard Letac; HΓ©lΓ¨ne Massam; Donald Richards πŸ“‚ Article πŸ“… 2001 πŸ› Elsevier Science 🌐 English βš– 175 KB

Suppose that the random vector (X 1 , ..., X q ) follows a Dirichlet distribution on R q + with parameter ( p 1 , ..., p q ) # R q + . For f 1 , ..., f q >0, it is well-known that . In this paper, we generalize this expectation formula to the singular and non-singular multivariate Dirichlet distrib

Use of Moments in Distribution Theory: A
✍ N.A. Volodin; S. Kotz; N.L. Johnson πŸ“‚ Article πŸ“… 1993 πŸ› Elsevier Science 🌐 English βš– 189 KB

In recent papers, Johnson and Kotz (Amer. Statist. 44, 245-249 (1990); Math. Sci. 15, 42-52 (1990)) have explored the utility of moment calculations as a simple way of establishing distributional forms. In particular a characterization theorem for beta distributions has been proved. In this paper th

Properties of Prior and Posterior Distri
✍ Ming-Hui Chen; Qi-Man Shao πŸ“‚ Article πŸ“… 1999 πŸ› Elsevier Science 🌐 English βš– 162 KB

In this article, we model multivariate categorical (binary and ordinal) response data using a very rich class of scale mixture of multivariate normal (SMMVN) link functions to accommodate heavy tailed distributions. We consider both noninformative as well as informative prior distributions for SMMVN

The Construction of Multivariate Distrib
✍ Mark S Kaiser; Noel Cressie πŸ“‚ Article πŸ“… 2000 πŸ› Elsevier Science 🌐 English βš– 209 KB

We address the problem of constructing and identifying a valid joint probability density function from a set of specified conditional densities. The approach taken is based on the development of relations between the joint and the conditional densities using Markov random fields (MRFs). We give a ne