04197nam 22006614a 450 991014503550332120180731044224.01-280-28810-897866102881060-470-24458-50-471-74313-50-471-74312-7(CKB)1000000000239335(EBL)243673(OCoLC)70701307(SSID)ssj0000204680(PQKBManifestationID)11171138(PQKBTitleCode)TC0000204680(PQKBWorkID)10188050(PQKB)11560169(MiAaPQ)EBC243673(EXLCZ)99100000000023933520050218d2006 uy 0engur|n|---|||||txtccrModes of parametric statistical inference[electronic resource] /Seymour Geisser with the assistance of Wesley JohnsonHoboken, N.J. Wiley-Intersciencec20061 online resource (218 p.)Wiley series in probability and statisticsDescription based upon print version of record.0-471-66726-9 Includes bibliographical references and index.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); References6. 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 MLE7.13 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; IndexA 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 fromWiley series in probability and statistics.ProbabilitiesMathematical statisticsDistribution (Probability theory)Electronic books.Probabilities.Mathematical statistics.Distribution (Probability theory)519.5/4519.54Geisser Seymour102951Johnson Wesley O955850MiAaPQMiAaPQMiAaPQBOOK9910145035503321Modes of parametric statistical inference2163526UNINA