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The Resource A Comparison of the Bayesian and Frequentist Approaches to Estimation, by Francisco J. Samaniego, (electronic resource)
A Comparison of the Bayesian and Frequentist Approaches to Estimation, by Francisco J. Samaniego, (electronic resource)
Resource Information
The item A Comparison of the Bayesian and Frequentist Approaches to Estimation, by Francisco J. Samaniego, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Oklahoma Libraries.This item is available to borrow from all library branches.
Resource Information
The item A Comparison of the Bayesian and Frequentist Approaches to Estimation, by Francisco J. Samaniego, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Oklahoma Libraries.
This item is available to borrow from all library branches.
 Summary
 This monograph contributes to the area of comparative statistical inference. Attention is restricted to the important subfield of statistical estimation. The book is intended for an audience having a solid grounding in probability and statistics at the level of the yearlong undergraduate course taken by statistics and mathematics majors. The necessary background on Decision Theory and the frequentist and Bayesian approaches to estimation is presented and carefully discussed in Chapters 1–3. The “threshold problem”  identifying the boundary between Bayes estimators which tend to outperform standard frequentist estimators and Bayes estimators which don’t  is formulated in an analytically tractable way in Chapter 4. The formulation includes a specific (decisiontheory based) criterion for comparing estimators. The centerpiece of the monograph is Chapter 5 in which, under quite general conditions, an explicit solution to the threshold is obtained for the problem of estimating a scalar parameter under squared error loss. The six chapters that follow address a variety of other contexts in which the threshold problem can be productively treated. Included are treatments of the Bayesian consensus problem, the threshold problem for estimation problems involving of multidimensional parameters and/or asymmetric loss, the estimation of nonidentifiable parameters, empirical Bayes methods for combining data from ‘similar’ experiments and linear Bayes methods for combining data from ‘related’ experiments. The final chapter provides an overview of the monograph’s highlights and a discussion of areas and problems in need of further research. F. J. Samaniego is a Distinguished Professor of Statistics at the University of California, Davis. He served as Theory and Methods Editor of the Journal of the American Statistical Association (200305), was the 2004 recipient of the Davis Prize for Undergraduate Teaching and Scholarly Achievement, and is an elected Fellow of the ASA, the IMS and the RSS and an elected Member of the ISI
 Language

 eng
 eng
 Edition
 1st ed. 2010.
 Extent
 1 online resource (234 p.)
 Note
 Description based upon print version of record
 Contents

 Point Estimation from a DecisionTheoretic Viewpoint
 An Overview of the Frequentist Approach to Estimation
 An Overview of the Bayesian Approach to Estimation
 The Threshold Problem
 Comparing Bayesian and Frequentist Estimators of a Scalar Parameter
 Conjugacy, SelfConsistency and Bayesian Consensus
 Bayesian vs. Frequentist Shrinkage in Multivariate Normal Problems
 Comparing Bayesian and Frequentist Estimators under Asymmetric Loss
 The Treatment of Nonidentifiable Models
 Improving on Standard Bayesian and Frequentist Estimators
 Combining Data from “Related” Experiments
 Fatherly Advice
 Isbn
 9781441959416
 Label
 A Comparison of the Bayesian and Frequentist Approaches to Estimation
 Title
 A Comparison of the Bayesian and Frequentist Approaches to Estimation
 Statement of responsibility
 by Francisco J. Samaniego
 Language

 eng
 eng
 Summary
 This monograph contributes to the area of comparative statistical inference. Attention is restricted to the important subfield of statistical estimation. The book is intended for an audience having a solid grounding in probability and statistics at the level of the yearlong undergraduate course taken by statistics and mathematics majors. The necessary background on Decision Theory and the frequentist and Bayesian approaches to estimation is presented and carefully discussed in Chapters 1–3. The “threshold problem”  identifying the boundary between Bayes estimators which tend to outperform standard frequentist estimators and Bayes estimators which don’t  is formulated in an analytically tractable way in Chapter 4. The formulation includes a specific (decisiontheory based) criterion for comparing estimators. The centerpiece of the monograph is Chapter 5 in which, under quite general conditions, an explicit solution to the threshold is obtained for the problem of estimating a scalar parameter under squared error loss. The six chapters that follow address a variety of other contexts in which the threshold problem can be productively treated. Included are treatments of the Bayesian consensus problem, the threshold problem for estimation problems involving of multidimensional parameters and/or asymmetric loss, the estimation of nonidentifiable parameters, empirical Bayes methods for combining data from ‘similar’ experiments and linear Bayes methods for combining data from ‘related’ experiments. The final chapter provides an overview of the monograph’s highlights and a discussion of areas and problems in need of further research. F. J. Samaniego is a Distinguished Professor of Statistics at the University of California, Davis. He served as Theory and Methods Editor of the Journal of the American Statistical Association (200305), was the 2004 recipient of the Davis Prize for Undergraduate Teaching and Scholarly Achievement, and is an elected Fellow of the ASA, the IMS and the RSS and an elected Member of the ISI
 http://library.link/vocab/creatorName
 Samaniego, Francisco J
 Dewey number
 519.54
 http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut
 XYhsbZ3B_Ko
 Language note
 English
 LC call number

 QA273.A1274.9
 QA274274.9
 Literary form
 non fiction
 Nature of contents
 dictionaries
 Series statement
 Springer Series in Statistics,
 http://library.link/vocab/subjectName

 Distribution (Probability theory
 Mathematical statistics
 Social sciences
 Probability Theory and Stochastic Processes
 Statistical Theory and Methods
 Methodology of the Social Sciences
 Label
 A Comparison of the Bayesian and Frequentist Approaches to Estimation, by Francisco J. Samaniego, (electronic resource)
 Note
 Description based upon print version of record
 Bibliography note
 Includes bibliographical references (p. [213]219) and index
 Carrier category
 online resource
 Carrier category code

 cr
 Content category
 text
 Content type code

 txt
 Contents
 Point Estimation from a DecisionTheoretic Viewpoint  An Overview of the Frequentist Approach to Estimation  An Overview of the Bayesian Approach to Estimation  The Threshold Problem  Comparing Bayesian and Frequentist Estimators of a Scalar Parameter  Conjugacy, SelfConsistency and Bayesian Consensus  Bayesian vs. Frequentist Shrinkage in Multivariate Normal Problems  Comparing Bayesian and Frequentist Estimators under Asymmetric Loss  The Treatment of Nonidentifiable Models  Improving on Standard Bayesian and Frequentist Estimators  Combining Data from “Related” Experiments  Fatherly Advice
 Dimensions
 unknown
 Edition
 1st ed. 2010.
 Extent
 1 online resource (234 p.)
 Form of item
 online
 Isbn
 9781441959416
 Media category
 computer
 Media type code

 c
 Other control number
 10.1007/9781441959416
 Specific material designation
 remote
 System control number

 (CKB)2670000000047191
 (EBL)646418
 (OCoLC)654397519
 (SSID)ssj0000449209
 (PQKBManifestationID)11298184
 (PQKBTitleCode)TC0000449209
 (PQKBWorkID)10429240
 (PQKB)10571347
 (DEHe213)9781441959416
 (MiAaPQ)EBC646418
 (EXLCZ)992670000000047191
 Label
 A Comparison of the Bayesian and Frequentist Approaches to Estimation, by Francisco J. Samaniego, (electronic resource)
 Note
 Description based upon print version of record
 Bibliography note
 Includes bibliographical references (p. [213]219) and index
 Carrier category
 online resource
 Carrier category code

 cr
 Content category
 text
 Content type code

 txt
 Contents
 Point Estimation from a DecisionTheoretic Viewpoint  An Overview of the Frequentist Approach to Estimation  An Overview of the Bayesian Approach to Estimation  The Threshold Problem  Comparing Bayesian and Frequentist Estimators of a Scalar Parameter  Conjugacy, SelfConsistency and Bayesian Consensus  Bayesian vs. Frequentist Shrinkage in Multivariate Normal Problems  Comparing Bayesian and Frequentist Estimators under Asymmetric Loss  The Treatment of Nonidentifiable Models  Improving on Standard Bayesian and Frequentist Estimators  Combining Data from “Related” Experiments  Fatherly Advice
 Dimensions
 unknown
 Edition
 1st ed. 2010.
 Extent
 1 online resource (234 p.)
 Form of item
 online
 Isbn
 9781441959416
 Media category
 computer
 Media type code

 c
 Other control number
 10.1007/9781441959416
 Specific material designation
 remote
 System control number

 (CKB)2670000000047191
 (EBL)646418
 (OCoLC)654397519
 (SSID)ssj0000449209
 (PQKBManifestationID)11298184
 (PQKBTitleCode)TC0000449209
 (PQKBWorkID)10429240
 (PQKB)10571347
 (DEHe213)9781441959416
 (MiAaPQ)EBC646418
 (EXLCZ)992670000000047191
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