MARC Record from marc_columbia

LEADER: 04790cam a2200553Mu 4500
001 15138307
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006 m o d
007 cr |n|---|||||
008 190119s2018 flu o 000 0 eng d
035 $a(OCoLC)on1082974765
035 $a(NNC)15138307
040 $aEBLCP$beng$epn$cEBLCP$dYDX$dAU@$dOCLCQ$dTYFRS$dOCLCO$dOCLCF$dOCLCQ$dK6U$dOCLCO
066 $c(S
019 $a1082877748
020 $a9781351452878
020 $a1351452878
020 $z0824781236
020 $z9780824781231
035 $a(OCoLC)1082974765$z(OCoLC)1082877748
050 4 $aQA279.5.F56 1990
082 04 $a519.5/42
049 $aZCUA
100 1 $aFlorens, Jean-Pierre.
245 10 $aElements of Bayesian Statistics
260 $aBoca Raton :$bRoutledge,$c2018.
300 $a1 online resource (542 pages)
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aChapman and Hall/CRC Pure and Applied Mathematics ;$vv. 134
588 0 $aPrint version record.
505 8 $a1.2.1. General Definitions1.2.2. Dominated Experiments; 1.2.3. Three Remarks on Regular and Dominated Experiments; 1.2.4. A Remark Regarding the Interpretation of Bayesian Experiments; 1.2.5. A Remark on Sampling Theory and Bayesian Methods; 1.2.6. A Remark Regarding So-called "Improper" Prior Distributions; 1.2.7. Families of Bayesian Experiments; 1.3. Some Examples of Bayesian Experiments; 1.4. Reduction of Bayesian Experiments; 1.4.1. Introduction; 1.4.2. Marginal Experiments; 1.4.3. Conditional Experiment; 1.4.4. Complementary Reductions; 1.4.5. Dominance in Reduced Experiments
505 8 $a2: Admissible Reductions: Sufficiency and Ancillarity2.1. Introduction; 2.2. Conditional Independence; 2.2.1. Notation; 2.2.2. Definition of Conditional Independence; 2.2.3. Null Sets and Completion; 2.2.4. Basic Properties of Conditional Independence; 2.2.5. Conditional Independence and Densities; 2.2.6. Conditional Independence as Point Properties; 2.3. Admissible Reductions of an Unreduced Experiment; 2.3.1. Introduction; 2.3.2. Admissible Reductions on the Sample Space; 2.3.3. Admissible Reductions on the Parameter Space; 2.3.4. Some Comments on the Definitions
505 8 $a2.3.5. Elementary Properties of Sufficiency and Ancillarity2.3.6. Sufficiency and Ancillarity in a Dominated Experiment; 2.3.7. Sampling Theory and Bayesian Methods; 2.3.8. A First Result on the Relations between Sufficiency and Ancillarity; 3: Admissible Reductions in Reduced Experiments; 3.1. Introduction; 3.2. Admissible Reduction in Marginal Experiments; 3.2.1. Introduction; 3.2.2. Basic Concepts; 3.2.3. Sufficiency and Ancillarity in Unreduced and in Marginal Experiments; 3.2.4. A Remark on "Partial" Sufficiency; 3.3. Admissible Reductions in Conditional Experiments; 3.3.1. Introduction
505 8 $a3.3.2. Reductions in the Sample Space3.3.3. Reductions in the Parameter Space; 3.3.4. Elementary Properties; 3.3.5. Relationships between Sufficiency and Ancillarity; 3.3.6. Sufficiency and Ancillarity in a Dominated Reduced Experiment; 3.4. Jointly Admissible Reductions; 3.4.1. Mutual Sufficiency; 3.4.2. Mutual Exogeneity; 3.4.3. Bayesian Cut; 3.4.4. Joint Reductions in a Dominated Experiment; 3.4.5. Joint Reductions in a Conditional Experiment; 3.4.6. Some Examples; 3.5. Comparison of Experiments; 3.5.1. Comparison on the Sample Space: Sufficiency
500 $a3.5.2. Comparison on the Parameter Space: Encompassing
650 0 $aBayesian statistical decision theory.
650 6 $aThéorie de la décision bayésienne.
650 7 $aBayesian statistical decision theory.$2fast$0(OCoLC)fst00829019
655 0 $aElectronic books.
655 4 $aElectronic books.
700 1 $aMouchart, Micher.
700 1 $aRolin, Jean-Marie.
776 08 $iPrint version:$aFlorens, Jean-Pierre.$tElements of Bayesian Statistics.$dBoca Raton : Routledge, ©2018$z9780824781231
830 0 $aChapman and Hall/CRC Pure and Applied Mathematics.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15138307$zTaylor & Francis eBooks
880 0 $6505-00/(S$aCover; Half Title; Title Page; Copyright Page; Dedication; Table of Contents; Preface; Notation; 0: Basic Tools and Notation from Probability Theory; 0.1. Introduction; 0.2. Measurable Spaces; 0.2.1. σ-Fields; 0.2.2. Measurable Functions; 0.2.3. Product of Measurable Spaces; 0.2.4. Monotone Class Theorems; 0.3. Probability Spaces; 0.3.1. Measures and Integrals; 0.3.2. Probabilities. Expectations. Null Sets; 0.3.3. Transition and Product Probability; 0.3.4. Conditional Expectation; 0.3.5. Densities; 1: Bayesian Experiments; 1.1. Introduction; 1.2. The Basic Concepts of Bayesian Experiments
852 8 $blweb$hEBOOKS