Bayesian inference in regression with Pearson disturbances

In this paper we propose new estimation techniques in connection with regression models whose errors have distributions which are members of the celebrated Pearson’s system. Efficient MCMC procedures are proposed in the context of likelihood—based inference. The new techniques are applied to four major currencies.

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Year of publication:	2013
Authors:	Tsionas, Efthymios G.
Published in:	Economics Letters. - Elsevier, ISSN 0165-1765. - Vol. 118.2013, 1, p. 177-181
Publisher:	Elsevier
Subject:	Pearson distributions \| Likelihood function \| Posterior distribution \| MCMC \| Bayesian inference

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Type of publication:	Article
Classification:	C11 - Bayesian Analysis ; c46
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011041585