The Numerical Computation of Posterior Distributions in Bayesian Statistical Inference

Park M. Reilly

Journal of the Royal Statistical Society Series C, 1976, vol. 25, issue 3, 201-209

Abstract: A method is described in which distributions of parameters in problems of Bayesian statistical inference are handled as arrays in computer storage. This results in a very flexible approach to problems in nonlinear regression, fitting of frequency functions, model discrimination, etc. It is particularly valuable in finding marginal and conditional parameter distributions and distributions of functions of the parameters in a model. It does so with no requirements for linearization of models or for specific forms for distribution functions. If more than a few parameters are present the requirements for computer storage may be large.

Date: 1976
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.2307/2347227

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:25:y:1976:i:3:p:201-209

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().