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.
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DOI : 10.36106/ijsr
Cite This Article:
D. Sheeba Singh, M. Immaculate Mary Bayesian Estimation Of Posterior Risk
Of Tuberculosis Using Different Loss Functions International Journal of Scientific Research, Vol : 2, Issue : 9 September 2013
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D. Sheeba Singh, M. Immaculate Mary Bayesian Estimation Of Posterior Risk Of Tuberculosis Using Different Loss Functions International Journal of Scientific Research, Vol : 2, Issue : 9 September 2013
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