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Download PDF by Francisco J. Samaniego: A Comparison of the Bayesian and Frequentist Approaches to

By Francisco J. Samaniego

ISBN-10: 1441959408

ISBN-13: 9781441959409

ISBN-10: 1461426197

ISBN-13: 9781461426196

This monograph contributes to the realm of comparative statistical inference. awareness is specific to the $64000 subfield of statistical estimation. The ebook is meant for an viewers having a great grounding in likelihood and records on the point of the year-long undergraduate path taken through information and arithmetic majors. the mandatory historical past on selection idea and the frequentist and Bayesian methods to estimation is gifted and punctiliously mentioned in Chapters 1–3. The “threshold challenge” - making a choice on the boundary among Bayes estimators which are likely to outperform typical frequentist estimators and Bayes estimators which don’t - is formulated in an analytically tractable means in bankruptcy four. The formula features a particular (decision-theory dependent) criterion for evaluating estimators. the center piece of the monograph is bankruptcy five during which, less than particularly common stipulations, an particular approach to the edge is got for the matter of estimating a scalar parameter less than squared mistakes loss. The six chapters that persist with deal with a number of different contexts during which the brink challenge could be productively taken care of. incorporated are remedies of the Bayesian consensus challenge, the brink challenge for estimation difficulties related to of multi-dimensional parameters and/or uneven loss, the estimation of nonidentifiable parameters, empirical Bayes tools for combining info from ‘similar’ experiments and linear Bayes equipment for combining information from ‘related’ experiments. the ultimate bankruptcy presents an outline of the monograph’s highlights and a dialogue of components and difficulties wanting extra research.

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A Comparison of the Bayesian and Frequentist Approaches to Estimation (Springer Series in Statistics) by Francisco J. Samaniego

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