Modes of parametric statistical inference [[electronic resource] /] / Seymour Geisser with the assistance of Wesley Johnson

• Record Nr.: UNINA9910830797003321
• Autore: Geisser Seymour
• Pubbl/distr/stampa: Hoboken, N.J., : Wiley-Interscience, c2006
• ISBN: 1-280-28810-8; 9786610288106; 0-470-24458-5; 0-471-74313-5; 0-471-74312-7
• Descrizione fisica: 1 online resource (218 p.)
• Collana: Wiley series in probability and statistics
• Altri autori (Persone): JohnsonWesley O
• Disciplina: 519.5/4; 519.54
• Soggetti: Probabilities; Mathematical statistics; Distribution (Probability theory)
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: 4.2 Remarks on Size4.3 Uniformly Most Powerful Tests; 4.4 Neyman-Pearson Fundamental Lemma; 4.5 Monotone Likelihood Ratio Property; 4.6 Decision Theory; 4.7 Two-Sided Tests; References; 5. Unbiased and Invariant Tests; 5.1 Unbiased Tests; 5.2 Admissibility and Tests Similar on the Boundary; 5.3 Neyman Structure and Completeness; 5.4 Invariant Tests; 5.5 Locally Best Tests; 5.6 Test Construction; 5.7 Remarks on N-P Theory; 5.8 Further Remarks on N-P Theory; 5.9 Law of the Iterated Logarithm (LIL); 5.10 Sequential Analysis; 5.11 Sequential Probability Ratio Test (SPRT); References; 6. Elements of Bayesianism6.1 Bayesian Testing; 6.2 Testing a Composite vs. a Composite; 6.3 Some Remarks on Priors for the Binomial; 6.4 Coherence; 6.5 Model Selection; References; 7. Theories of Estimation; 7.1 Elements of Point Estimation; 7.2 Point Estimation; 7.3 Estimation Error Bounds; 7.4 Efficiency and Fisher Information; 7.5 Interpretations of Fisher Information; 7.6 The Information Matrix; 7.7 Sufficiency; 7.8 The Blackwell-Rao Result; 7.9 Bayesian Sufficiency; ; 7.10 Maximum Likelihood Estimation; 7.11 Consistency of the MLE; 7.12 Asymptotic Normality and "Efficiency" of the MLE; 7.13 Sufficiency PrinciplesReferences; 8. Set and Interval Estimation; 8.1 Confidence Intervals (Sets); 8.2 Criteria for Confidence Intervals; 8.3 Conditioning; 8.4 Bayesian Intervals (Sets); 8.5 Highest Probability Density (HPD) Intervals; 8.6 Fiducial Inference; 8.7 Relation Between Fiducial and Bayesian Distributions; 8.8 Several Parameters; 8.9 The Fisher-Behrens Problem; 8.10 Confidence Solutions; 8.11 The Fieller-Creasy Problem; References; References; Index
• Sommario/riassunto: A fascinating investigation into the foundations of statistical inferenceThis publication examines the distinct philosophical foundations of different statistical modes of parametric inference. Unlike many other texts that focus on methodology and applications, this book focuses on a rather unique combination of theoretical and foundational aspects that underlie the field of statistical inference. Readers gain a deeper understanding of the evolution and underlying logic of each mode as well as each mode's strengths and weaknesses.The book begins with fascinating highlights from