Inference Based on Complete Data

Eswar G. Phadia
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Eswar G. Phadia: William Paterson University of New Jersey, Department of Mathematics

Chapter Chapter 2 in Prior Processes and Their Applications, 2013, pp 109-153 from Springer

Abstract: Abstract This chapter contains various applications of prior processes discussed in the previous chapter in solving some inferential problems from a Bayesian point of view. It covers multitude of fields such as, estimation, hypothesis testing, empirical Bayes, density estimation, bioassay, etc. They are grouped according to the inferential task they signify. However, a bulk of the space is devoted to the Bayesian estimation of the distribution function, and its functional, with respect to different priors, and some common features are discussed. This is followed by confidence bands, two-sample problems, a regression problem, and some interesting additional applications are also mentioned. Finally, a decision theoretic approach to testing a statistical hypothesis regarding an unknown distribution function is indicated.

Keywords: Posterior Distribution; Loss Function; Dirichlet Process; Confidence Band; Bayesian Estimator (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-39280-1_2

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DOI: 10.1007/978-3-642-39280-1_2

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