Development of modern statistics and related topics: in celebration of Prof. Yaoting Zhang's 70th birthday
(eBook)
Contributors:
Series:
Published:
River Edge, NJ : World Scientific Pub. Co., 2003.
Format:
eBook
ISBN:
9789812796707, 9812796703, 9789812383952, 9812383956
Physical Desc:
1 online resource (xii, 287 pages) : illustrations
Status:
Ebsco (CCU)
Description
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 linkage analysis, use of mixture models in genetic studies, and design and analysis of quantitative traits.
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APA Citation (style guide)
Zhang, Y., Zhang, H., & Huang, J. (2003). Development of modern statistics and related topics: in celebration of Prof. Yaoting Zhang's 70th birthday. River Edge, NJ, World Scientific Pub. Co.
Chicago / Turabian - Author Date Citation (style guide)Zhang, Yaoting, 1933-, Heping. Zhang and Jian. Huang. 2003. Development of Modern Statistics and Related Topics: In Celebration of Prof. Yaoting Zhang's 70th Birthday. River Edge, NJ, World Scientific Pub. Co.
Chicago / Turabian - Humanities Citation (style guide)Zhang, Yaoting, 1933-, Heping. Zhang and Jian. Huang, Development of Modern Statistics and Related Topics: In Celebration of Prof. Yaoting Zhang's 70th Birthday. River Edge, NJ, World Scientific Pub. Co, 2003.
MLA Citation (style guide)Zhang, Yaoting, et al. Development of Modern Statistics and Related Topics: In Celebration of Prof. Yaoting Zhang's 70th Birthday. River Edge, NJ, World Scientific Pub. Co, 2003.
Note! Citation formats are based on standards as of July 2022. Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy.
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Language:
English
Notes
Bibliography
Includes bibliographical references.
Description
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 linkage analysis, use of mixture models in genetic studies, and design and analysis of quantitative traits.
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Grouped Work ID:
ae38e76b-caaa-6b7c-f4d4-ef29a3201bde
Record Information
| Last File Modification Time | Apr 05, 2024 09:18:30 PM |
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| Last Grouped Work Modification Time | Apr 05, 2024 09:12:39 PM |
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| 245 | 0 | 0 | |a Development of modern statistics and related topics :|b in celebration of Prof. Yaoting Zhang's 70th birthday /|c edited by Heping Zhang, Jian Huang. |
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| 505 | 0 | |a An interview with Professor Yaoting Zhang / Qiwei Yao and Zhaohai Li -- Significance level in interval mapping / David O. Siegmund and Benny Yakir -- An asymptotic Pythagorean identity / Zhiliang Ying -- A Monte Carlo gap test in computing HPD regions / Ming-Hui Chen [and others] -- Estimating restricted normal means using the EM-type algorithms and IBF sampling / Ming Tan, Guo-Liang Tian and Hong-Bin Fang -- An example of algorithm mining: covariance adjustment to accelerate EM and Gibbs / Chuanhai Liu -- Large deviations and deviation inequality for kernel density estimator in L[symbol]-distance / Liangzhen Lei, Liming Wu and Bin Xie -- Local sensitivity analysis of model misspecification / Guobing Lu -- Empirical likelihood confidence intervals for the difference of two quantiles of a population / Yongsong Qin and Yuehua Wu -- Exponential inequalities for spatial processes and uniform convergence rates for density estimation / Qiwei Yao -- A skew regression model for inference of stock volatility / Tuhao J. Chen and Hanfeng Chen -- Explicit transitional dynamics in growth models / Danyang Xie -- A fiscal federalism approach to optimal taxation and intergovernmental transfers in a dynamic model / Liutang Gong and Heng-Fu Zou -- Sharing catastrophe risk under model uncertainty / Xiaodong Zhu -- Ranked set sampling: a methodology for observational economy / Zehua Chen -- Some recent advances on response-adaptive randomized designs / Feifang Hu -- A childhood epidemic model with birthrate-dependent transmission / Yingcun Xia -- Linear regression analysis with observations subject to interval censoring / Linxiong Li -- When can the Haseman-Elston procedure for quantitative trait loci be improved? Insights from optimal design theory / Zhaohai Li, Minyu Xie and Joseph L. Gastwirth -- A semiparametric method for mapping quantitative trait loci / Jian Huang and Kai Wang -- Structure mixture regression models / Hongtu Zhu and Heping Zhang. | |
| 520 | |a 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 linkage analysis, use of mixture models in genetic studies, and design and analysis of quantitative traits. | ||
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