Bayesian Analysis of Gumbel Type II Distribution under Censored Data
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The book is an interesting piece of work for the research students especially in the field of Bayesian inference. The fundamental purpose of the book is to develop the basic understanding about the methods to carry out the Bayesian analysis of some probability distribution(s) under complete and censored samples using different priors and loss functions. The simple simulation study proposed in the book will facilitate the students and researchers to understand how the parameters of the models can be estimated numerically under a Bayesian framework. As the predicted values are the important comp...
The book is an interesting piece of work for the research students especially in the field of Bayesian inference. The fundamental purpose of the book is to develop the basic understanding about the methods to carry out the Bayesian analysis of some probability distribution(s) under complete and censored samples using different priors and loss functions. The simple simulation study proposed in the book will facilitate the students and researchers to understand how the parameters of the models can be estimated numerically under a Bayesian framework. As the predicted values are the important component of statistical analysis, we have proposed posterior predictive intervals to predict the future values under the Bayesian inference. The comparison among the performance of different estimators has been made under the analysis of simulated and real life data sets. We hope that the students/researchers will find this book as a facilitating effort for their learning in the field of Bayesian inference.
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