Volume : IV, Issue : III, March - 2014

Bayesian Inference for Bernoulli Distribution Using Different Loss Functions

D. Sheeba Singh, M. Immaculate Mary

Abstract :

Bayesian estimation and inference has a number of advantages in statistical modelling and data analysis. It provides a way of formalising the process of learning from data to update beliefs in accord with recent notions of knowledge synthesis.In this paper the Bernoulli distribution is taken for Bayesian analysis. The properties of Bayes estimates of the parameters are studied under different loss functions through simulated and real life data. Different priors like informative and non–informative are used to estimate the parameters. The loss functions are compared through posterior risk.

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Article: Download PDF   DOI : 10.36106/ijar  

Cite This Article:

D. Sheeba Singh, M. Immaculate Mary Bayesian Inference for Bernoulli Distribution Using Different Loss Functions Indian Journal of Applied Research, Vol.IV, Issue. III

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