Bayesian estimation of incomplete data using conditionally specified priors

Sarabia, JM and Shahtahmassebi, G ORCID: https://orcid.org/0000-0002-0630-2750, 2017. Bayesian estimation of incomplete data using conditionally specified priors. Communications in Statistics - Simulation and Computation, 46 (5), pp. 3419-3435. ISSN 0361-0918

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Abstract

In this paper, a class of conjugate prior for estimating incomplete count data based on a broad class of conjugate prior distributions is presented. The new class of prior distributions arises from a conditional perspective, making use of the conditional specification methodology and can be considered as the generalisation of the form of prior distributions that have been used previously in the estimation of in- complete count data well. Finally, some examples of simulated and real data are given.

Item Type:	Journal article
Publication Title:	Communications in Statistics - Simulation and Computation
Creators:	Sarabia, J.M. and Shahtahmassebi, G.
Publisher:	Taylor & Francis
Date:	2017
Volume:	46
Number:	5
ISSN:	0361-0918
Identifiers:	Number Type 10.1080/03610918.2015.1091076 DOI
Divisions:	Schools > School of Science and Technology
Record created by:	Linda Sullivan
Date Added:	12 Feb 2016 08:55
Last Modified:	07 Jun 2019 10:04
URI:	https://irep.ntu.ac.uk/id/eprint/26938

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