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

Format:

Book

Contributor:

Zhang, Yaoting, 1933-

Zhang, Heping.

Huang, Jian.

Series:

Series in biostatistics ; v. 1.

Series in biostatistics ; v. 1

Language:

English

Subjects (All):

Statistics.

Physical Description:

1 online resource (301 p.)

Edition:

1st ed.

Place of Publication:

River Edge, NJ : World Scientific Pub. Co., c2003.

Language Note:

English

Summary:

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

Contents:

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

Notes:

Description based upon print version of record.

Includes bibliographical references.

ISBN:

9786611956097

9781281956095

1281956090

9789812796707

9812796703

OCLC:

879023615