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|a QA279.5.F56 1990
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|c (S
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| 100 |
1 |
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|a Florens, Jean-Pierre.
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| 245 |
1 |
0 |
|a Elements of Bayesian Statistics
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| 260 |
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|a Boca Raton :
|b Routledge,
|c 2018.
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| 300 |
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|a 1 online resource (542 pages)
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| 336 |
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|a text
|b txt
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|a Chapman and Hall/CRC Pure and Applied Mathematics ;
|v v. 134
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0 |
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|a Print version record.
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| 505 |
8 |
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|a 1.2.1. 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
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| 505 |
8 |
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|a 2: 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
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|a 2.3.5. 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
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| 505 |
8 |
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|a 3.3.2. 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
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| 500 |
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|a 3.5.2. Comparison on the Parameter Space: Encompassing
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| 650 |
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0 |
|a Bayesian statistical decision theory.
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| 650 |
|
7 |
|a Bayesian statistical decision theory
|2 fast
|
| 700 |
1 |
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|a Mouchart, Micher.
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| 700 |
1 |
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|a Rolin, Jean-Marie.
|
| 776 |
0 |
8 |
|i Print version:
|a Florens, Jean-Pierre.
|t Elements of Bayesian Statistics.
|d Boca Raton : Routledge, ©2018
|z 9780824781231
|
| 830 |
|
0 |
|a Chapman and Hall/CRC Pure and Applied Mathematics.
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|z Full Text (via Taylor & Francis)
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|a Cover; 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
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