Bayesian Estimation Of Posterior Risk  Of Tuberculosis Using Different Loss  Functions

D. Sheeba Singh; M. Immaculate Mary

Volume : II, Issue : IX, September - 2013

Bayesian Estimation Of Posterior Risk Of Tuberculosis Using Different Loss Functions

D. Sheeba Singh, M. Immaculate Mary

Abstract :

The Bayesian estimation approach is a non–classical device in the estimation part of statistical inference which is very useful in real world situation. In Bayesian estimation loss function, prior distribution and posterior distribution are the most important ingredients. The conjugate prior, uniform prior and the Jeffrey�s prior are considered for finding the Bayes estimator. The objective of this paper is to examine the effects of TB incidence in the 30 districts of Tamilnadu in the year 2011–2012 using different priors. The relative risk for each sub region of the study area has been estimated. The posterior probabilities have been calculated to find the risk of the disease throughout the state of Tamilnadu and the Bayes shrinkage estimates have also been calculated. Bayes estimators of the parameters are studied under different symmetric and asymmetric loss functions.