Articles liés à Posterior Analysis for the Maxwell Model: Theory, Method...

Posterior Analysis for the Maxwell Model: Theory, Method and Computation - Couverture souple

Kazmi, Syed Mohsin Ali; Aslam, Muhammad; Ali, Sajid

 
9783659224782: Posterior Analysis for the Maxwell Model: Theory, Method and Computation
Couverture souple
ISBN 10 : 3659224782 ISBN 13 : 9783659224782
Editeur : LAP LAMBERT Academic Publishing, 2012

Synopsis

The Bayesian approach to analyze different statistical models has developed great interest among analysts. Posterior distribution is the workbench of the Bayesian statisticians. It is obtained when prior information is combined with likelihood. Therefore the prior information is necessary for the Bayesian approach. The prior information is purely subjective assessment of an expert before any data have been observed. So here we consider different informative and non-informative priors and compare them to see which one is more suitable for our proposed model. The effort of current study is to explore the heterogeneous population using the Bayesian analysis for simple and mixture of the Maxwell distribution when data is censored and uncensored. Various types of comparisons of prior distributions for the parameter of the Maxwell distribution and loss functions are illustrated. We also consider Type I mixture of the Maxwell distribution which is member of the subclass of the exponential family. As an extension to this work, a comparisons of different loss functions are made. Moreover we have derived the limiting expressions for the Bayes estimators with their variances.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

The Bayesian approach to analyze different statistical models has developed great interest among analysts. Posterior distribution is the workbench of the Bayesian statisticians. It is obtained when prior information is combined with likelihood. Therefore the prior information is necessary for the Bayesian approach. The prior information is purely subjective assessment of an expert before any data have been observed. So here we consider different informative and non-informative priors and compare them to see which one is more suitable for our proposed model. The effort of current study is to explore the heterogeneous population using the Bayesian analysis for simple and mixture of the Maxwell distribution when data is censored and uncensored. Various types of comparisons of prior distributions for the parameter of the Maxwell distribution and loss functions are illustrated. We also consider Type I mixture of the Maxwell distribution which is member of the subclass of the exponential family. As an extension to this work, a comparisons of different loss functions are made. Moreover we have derived the limiting expressions for the Bayes estimators with their variances.

Biographie de l'auteur

The author did his Master of Philosophy (M.Phil) in Statistics from Quaid-i-Azam University, Islamabad, Pakistan. Currently he is working as a Monitoring & Evaluation Officer at Sustainable Development Policy Institute (SDPI) Islamabad, Pakistan. His area of interest is Bayesian Analysis and Survey Sampling.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2012
Langue
anglais
ISBN 10 
3659224782
ISBN 13 
9783659224782
Reliure
Broché
Nombre de pages
140
Coordonnées du fabricant
non disponible
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