Development of modern statistics and related topics : in celebration of Prof. Yaoting Zhang's 70th birthday / / edited by Heping Zhang, Jian Huang

• Record Nr.: UNINA9910813734003321
• Pubbl/distr/stampa: River Edge, NJ, : World Scientific Pub. Co., c2003
• ISBN: 1-281-95609-0; 9786611956097; 981-279-670-3
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (301 p.)
• Collana: Series in biostatistics ; ; v. 1
• Altri autori (Persone): ZhangYaoting <1933->; ZhangHeping; HuangJian
• Disciplina: 519.5
• Soggetti: Statistics
• 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.
• Nota di contenuto: Contents ; Preface ; An Interview with Professor Yaoting Zhang ; Growing Up ; Professor Paolu Hsu and Statistics ; During the 'Culture Revolution' ; After 'Culture Revolution' ; I am Proud of My Students ; Significance Level in Interval Mapping ; 1. Introduction ; 2. Known Results; 3. A Combined Approximation 4. The Interval Mapping Process in the Gaussian Limit ; 5. Likelihood Ratio Transformation ; 6. Rice-Davies Approximation ; 7. Evaluation of (9) ; 8. Remarks ; References ; An Asymptotic Pythagorean Identity ; 1. Introduction; 2. Pythagorean Identity for Variance Calculation 3. Examples ; 4. Remarks ; References ; A Monte Carlo Gap Test in Computing HPD Regions ; 1. Introduction ; 2. Current Monte Carlo Methods ; 3. Monte Carlo Gap Tests ; 4. A Simulation Study ; ; 5. Concluding Remarks ; References; Estimating Restricted Normal Means Using the EM-type Algorithms and IBF Sampling 1. Introduction ; 2. Nonproduct versus Product Parameter Space ; 3. Estimation When Variances Are Known ; 4. Estimation when variances are Unknown ; 5. Applications ; 6. Discussion ; References; An Example of Algorithm Mining: Covariance Adjustment to Accelerate EM and Gibbs 1. An Overview ; 2. The Student-t Distribution ; 3. The EM Algorithm ; 4. The DA Algorithm ; 5. The PX-EM Algorithm ; 6. The PX-DA Algorithm ; 7. The CA-DA Algorithm ; 8. Discussion ; References; Large Deviations and Deviation Inequality for Kernel Density Estimator in L1(RD)-distance
• Sommario/riassunto: This book encompasses a wide range of important topics. The articles cover the following areas: asymptotic theory and inference, biostatistics, economics and finance, statistical computing and Bayesian statistics, and statistical genetics. Specifically, the issues that are studied include large deviation, deviation inequalities, local sensitivity of model misspecification in likelihood inference, empirical likelihood confidence intervals, uniform convergence rates in density estimation, randomized designs in clinical trials, MCMC and EM algorithms, approximation of p-values in multipoint link