LEADER 05409nam 2200649Ia 450 001 9910876907203321 005 20200520144314.0 010 $a1-283-27401-9 010 $a9786613274014 010 $a1-118-16592-6 010 $a1-118-16591-8 035 $a(CKB)2550000000054258 035 $a(EBL)818934 035 $a(OCoLC)757486971 035 $a(SSID)ssj0000541173 035 $a(PQKBManifestationID)11346601 035 $a(PQKBTitleCode)TC0000541173 035 $a(PQKBWorkID)10493594 035 $a(PQKB)11393341 035 $a(MiAaPQ)EBC818934 035 $a(EXLCZ)992550000000054258 100 $a19960724d1997 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSequential estimation /$fMalay Ghosh, Nitis Mukhopadhyay, Pranab K. Sen 210 $aNew York $cWiley$dc1997 215 $a1 online resource (504 p.) 225 1 $aWiley series in probability and statistics. Probability and statistics 300 $aDescription based upon print version of record. 311 $a0-471-81271-4 320 $aIncludes bibliographical references and indexes. 327 $aSequential Estimation; Contents; Preface; 1. Introduction and Coverage; 1.1 Introduction; 1.2 Some Sequential Sampling Schemes in Practice; 1.2.1 Binomial Waiting-Time Distribution; 1.2.2 Hypergeometric Waiting-Time Distribution; 1.2.3 Capture-Mark-Recapture Procedures; 1.2.4 Time-Sequential Models; 1.2.5 Sequential Models in Reliability Problems; 1.2.6 Recursive Estimation and Sequential Schemes; 1.3 Organization of This Book; 2. Probabilistic Results in Sequential Analysis; 2.1 Introduction; 2.2 Martingales; 2.3 Stopping Times; 2.4 Martingale Inequalities and Identities 327 $a2.5 Submartingale Convergence Theorems2.6 Martingale Central Limit Theorems; 2.7 Random Central Limit Theorems and Berry-Esseen Bounds; 2.8 Renewal Theorem-First Passage and Residual Waiting Times; 2.9 Nonlinear Renewal Theory; 2.10 Exercises; 3. Some Basic Concepts for Fixed-Sample Estimation; 3.1 Introduction; 3.2 Decision-Theoretic Notions; 3.3 Bayesian Decision Rules; 3.4 Sufficiency and Efficiency; 3.5 Invariance and Transitivity; 3.6 Method of Maximum Likelihood; 3.7 Why Sequential?; 3.8 Exercises; 4. General Aspects of Sequential Estimation; 4.1 Introduction 327 $a4.2 Sufficiency, Rao-Blackwell Theorem, and Transitivity4.3 Crame?r-Rao and Related Inequalities; 4.4 Sequential Binomial Sampling Plans; 4.5 Exercises; 5. Sequential Bayesian Estimation; 5.1 Introduction; 5.2 Bayesian Sequential Decision Rules; 5.3 Sequential Bayesian Estimation; 5.4 Asymptotically Pointwise Optimal (APO) Stopping Rules; 5.5 Hierarchical and Empirical Bayes Sequential Estimation; 5.6 Exercises; 6. Multistage Estimation; 6.1 Introduction; 6.2 Fixed-Width Confidence Intervals and Two-Stage Procedures; 6.2.1 Stein's Two-Stage Procedure; 6.2.2 Modified Two-Stage Procedure 327 $a6.2.3 Further Generalizations6.3 Fixed-Width Confidence Intervals and Three-Stage Procedures; 6.3.1 The Global Theory; 6.3.2 Applications of the Three-Stage Procedure; 6.4 Fixed-Width Confidence Intervals and Accelerated Sequential Procedures; 6.4.1 The Global Theory; 6.5 Point Estimation Problems; 6.5.1 Minimum Risk Normal Mean Problem; 6.5.2 Two-Stage Procedure; 6.5.3 Modified Two-Stage Procedure; 6.5.4 Three-Stage Procedure; 6.5.5 Accelerated Sequential Procedure; 6.6 Other Related Estimation Problems; 6.6.1 Point Estimation in Exponential Populations; 6.6.2 Estimation of Normal Variance 327 $a6.6.3 Binomial and Negative Binomial Problems6.7 Comparison of Populations; 6.7.1 Fixed-Width Confidence Intervals; 6.7.2 Point Estimation; 6.8 Estimation in Multivariate Normal and Linear Models; 6.8.1 Estimation of Mean Vector When ? Is Arbitrary; 6.8.2 Comparison of Populations; 6.8.3 Linear Regression Problems; 6.8.4 Shrinkage Estimators; 6.8.5 Estimation of Ordered Parameters; 6.9 Exercises; 7. Parametric Sequential Point Estimation; 7.1 Introduction; 7.2 Estimation of the Normal Mean; 7.3 Estimation of the Difference of Two Normal Means; 7.4 Point Estimation in Linear Models 327 $a7.5 Estimation of the Multivariate Normal Mean 330 $aThe only comprehensive guide to the theory and practice of one of today's most important probabilistic techniquesThe past 15 years have witnessed many significant advances in sequential estimation, especially in the areas of three-stage and nonparametric methodology. Yet, until now, there were no references devoted exclusively to this rapidly growing statistical field.Sequential Estimation is the first, single-source guide to the theory and practice of both classical and modern sequential estimation techniques--including parametric and nonparametric methods. Researchers in sequ 410 0$aWiley series in probability and statistics.$pProbability and statistics. 606 $aEstimation theory 606 $aSequential analysis 615 0$aEstimation theory. 615 0$aSequential analysis. 676 $a519.5/42 700 $aGhosh$b Malay$0534774 701 $aMukhopadhyay$b Nitis$f1950-$0256035 701 $aSen$b Pranab Kumar$f1937-$012024 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910876907203321 996 $aSequential estimation$91128681 997 $aUNINA