Comparing Bayesian and Likelihood Approaches to Parameter Estimation of a Negative Binomial Distribution

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG42__%2F10%3A00427046" target="_blank" >RIV/60162694:G42__/10:00427046 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26210/10:PU87475
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Comparing Bayesian and Likelihood Approaches to Parameter Estimation of a Negative Binomial Distribution
Original language description
It is well known that the maximum-likelihood estimates of a negative binomial distribution are biased and their numerical calculation tends to be error-prone for some extremal parameter values. In this case, it is necessary to find a different approach.A good approach seems to be a Bayesian one. The paper aims to compare both approaches. Using simulations it is shown that a Bayesian approach produces good results even in cases when the likelihood one fails. Moreover, estimators obtained using the Bayesian approach seems to be as good as bias corrected likelihood estimators as well as the numerically simpler quasi-likelihood estimators. Finally, based on the simulation results a recommendation is formulated that leads to obtaining optimal estimators for arbitrary parameter values. A system of Matlab programmes for calculating the estimates in question can be obtained from the first author.
Czech name
—
Czech description
—

Project
<a href="/en/project/1M06047" target="_blank" >1M06047: Research Center for Quality and Reliability of Production</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)