Year: 2006
Type: preprint
Abstract: The computation of two Bayesian predictive distributions which are discrete mixtures of incomplete beta functions is considered. The number of iterations can easily become large for these distributions and thus, the accuracy of the result can be questionable. Therefore, existing algorithms for that class of mixtures are improved by introducing round-off error calculation into the stopping rule. A further simple modification is proposed to deal with possible underflows that may prevent recurrence to work properly.
Source: arXiv (Cornell University)
Authors: Poitevineau, Jacques, Lecoutre, Bruno
Institution: Laboratoire de Mathématiques Raphaël Salem
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1501040539