Robustness of Bayesian results for Inverse Gaussian distribution under ML-II epsilon-contaminated and Edgeworth Series class of prior distributions
AbstractThis paper aims to study the sensitivity of Bayes estimate of location parameter of an Inverse Gaussian (IG) distribution to misspecification in the prior distribution. It also studies the effect of misspecification of the prior distribution on two-sided predictive limits for a future observation from IG population. Two prior distributions, a class ML-II ε-contaminated and Edgeworth Series (ESD), are employed for the location parameter of an IG distribution, to investigate the effect of misspecification in the priors. The numerical illustrations suggest that moderate amount of misspecification in prior distributions belonging to the class of ML-II ε-contaminated and ESD does not affect the Bayesian results.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 15396.
Date of creation: 17 May 2009
Date of revision:
Bayesian results; Inverse Gaussian distribution; ML-II ε-contaminated prior; Edgeworth Series Distributions;
Find related papers by JEL classification:
- C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
- C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
- C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
- A10 - General Economics and Teaching - - General Economics - - - General
- C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
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