LEADER 05374nam 2200649 a 450 001 996213512303316 005 20230421052039.0 010 $a1-282-25164-3 010 $a9786613813909 010 $a1-118-03319-1 010 $a1-118-03144-X 035 $a(CKB)2560000000055411 035 $a(EBL)696442 035 $a(OCoLC)760256420 035 $a(SSID)ssj0000482922 035 $a(PQKBManifestationID)11325485 035 $a(PQKBTitleCode)TC0000482922 035 $a(PQKBWorkID)10527203 035 $a(PQKB)11023058 035 $a(MiAaPQ)EBC696442 035 $a(EXLCZ)992560000000055411 100 $a19920116e19921973 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aBayesian inference in statistical analysis$b[electronic resource] /$fGeorge E.P. Box, George C. Tiao 205 $aWiley classics library ed. 210 $aNew York $cWiley$d1992 215 $a1 online resource (610 p.) 225 1 $aWiley Classics Library ;$vv.40 300 $aOriginally published: Reading, Mass. : Addison-Wesley Pub. Co., c1973. 300 $a"A Wiley-Interscience publication." 311 $a0-471-57428-7 320 $aIncludes bibliographical references (p. 571-579) and indexes. 327 $aBAYESIAN INFERENCE IN STATISTICAL ANALYSIS; CONTENTS; Chapter 1 Nature of Bayesian Inference; 1.1 Introduction and summary; 1.1.1 The role of statistical methods in scientific investigation; 1.1.2 Statistical inference as one part of statistical analysis; 1.1.3 The question of adequacy of assumptions; 1.1.4 An iterative process of model building in statistical analysis; 1.1.5 The role of Bayesian analysis; 1.2 Nature of Bayesian inference; 1.2.1 Bayes' theorem; 1.2.2 Application of Bayes' theorem with probability interpreted as frequencies 327 $a1.2.3 Application of Bayes' theorem with subjective probabilities1.2.4 Bayesian decision problems; 1.2.5 Application of Bayesian analysis to scientific inference; 1.3 Noninformative prior distributions; 1.3.1 The Normal mean ?(?2 known); 1.3.2 The Normal standard deviation ?(? known); 1.3.3 Exact data translated likelihoods and noninformative priors; 1.3.4 Approximate data translated likelihood; 1.3.5 Jeffreys' rule, information measure, and noninformative priors; 1.3.6 Noninformative priors for multiple parameters; 1.3.7 Noninformative prior distributions: A summary 327 $a1.4 Sufficient statistics1.4.1 Relevance of sufficient statistics in Bayesian inference; 1.4.2 An example using the Cauchy distribution; 1.5 Constraints on parameters; 1.6 Nuisance parameters; 1.6.1 Application to robustness studies; 1.6.2 Caution in integrating out nuisance parameters; 1.7 Systems of inference; 1.7.1 Fiducial inference and likelihood inference; Appendix A1.1 Combination of a Normal prior and a Normal likelihood; Chapter 2 Standard Normal Theory Inference Problems; 2.1 Introduction; 2.1.1 The Normal distribution; 2.1.2 Common Normal-theory problems 327 $a2.1.3 Distributional assumptions2.2 Inferences concerning a single mean from observations assuming common known variance; 2.2.1 An example; 2.2.2 Bayesian intervals; 2.2.3 Parallel results from sampling theory; 2.3 Inferences concerning the spread of a Normal distribution from observations having common known mean; 2.3.1 The inverted ?2, inverted ?, and the log ? distributions; 2.3.2 Inferences about the spread of a Normal distribution; 2.3.3 An example; 2.3.4 Relationship to sampling theory results; 2.4 Inferences when both mean and standard deviation are unknown; 2.4.1 An example 327 $a2.4.2 Component distributions of p(?, ? | y)2.4.3 Posterior intervals for ?; 2.4.4 Geometric interpretation of the derivation of p(? | y); 2.4.5 Informative prior distribution of ?; 2.4.6 Effect of changing the metric of ? for locally uniform prior; 2.4.7 Elimination of the nuisance parameter ? in Bayesian and sampling theories; 2.5 Inferences concerning the difference between two means; 2.5.1 Distribution oft ?2 - ?1 when ?21 = ?22; 2.5.2 Distribution of ?2 - ?1 when ?21 and ?22 are not assumed equal; 2.5.3 Approximations to the Behrens-Fisher distribution; 2.5.4 An example 327 $a2.6 Inferences concerning a variance ratio 330 $aThe Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson The Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Rob 410 0$aWiley Classics Library 606 $aMathematical statistics 615 0$aMathematical statistics. 676 $a519.54 676 $a519.542 700 $aBox$b George E. P$030397 701 $aTiao$b George C.$f1933-$047917 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996213512303316 996 $aBayesian inference in statistical analysis$964509 997 $aUNISA