Bayesian inference in regression with Pearson disturbances
AbstractIn 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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Bibliographic InfoArticle provided by Elsevier in its journal Economics Letters.
Volume (Year): 118 (2013)
Issue (Month): 1 ()
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Web page: http://www.elsevier.com/locate/ecolet
Pearson distributions; Likelihood function; Posterior distribution; MCMC; Bayesian inference;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
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