2008-06-23

2008统计学国际论坛

（2008年6月21-22日，北京•中国）

1. 学术委员会名单  2

2. 组委会名单  4

3. 会议日程表   5

4. 与会者报告摘要（按报告顺序）

（1）逸夫第一报告厅   17

（2）分会场一   21

（3）分会场二   37

（4）分会场三   52

（5）分会场四   69

（6）分会场五   86

（7）其他来稿   101

5.  附件

2008统计学国际论坛学术委员会

2008年统计学国际论坛会议组委员

2008统计学国际论坛日程表

Schedule of International Statistics Forum 2008

6月21日  (逸夫第一报告厅)

8:00-9:00报到

9:00-9:20 开幕式   (主持人：金勇进)

9:20-9:30 合影

9:30-9:50 茶歇

9:50-10:30 许宪春 国家统计局

10:30-11:10 贺铿 九三学社

11:10-11:50 袁卫 中国人民大学

12:00 -13:30 午餐 地点:中区食堂三层餐厅

13:30-14:10 赵民德 台湾中央研究院统计研究所

14:10-14:50 邵军 University of Wisconsin

14:50-15:30 蔡建文 University of North Carolina

15:30-15:50 茶歇

15:50:16:30 张南 日本广岛修道大学

16:30-17:10 王武保 美国默克制药公司生物统计和研究决策科学部

17:30--  欢迎晚宴  地点:中区食堂三层餐厅

6月22日 分会场1（明德主楼0404教室）

8：10-8：30 李冰，Department of Statistics ，Pennsylvania State University

8：30-8：50 朱力行，香港浸会大学数学系

8：50-9：10   耿直，北京大学数学科学学院概率统计系

9：10-9：30 石磊，云南财经大学统计与数学学院

9：30-9：50 mustafa mohamed abdalla，economics faculty of economic and social studies university of Khartoum

9：50-10：10 茶歇（明德主楼4层）

10：10-10：30 Zhengjun Zhang，University of Wisconsin

10：30-10：50 Xiangrong Yin，Department of Statistics, University of Georgia

10：50-11：10 闫军，Department of Statistics University of Connecticut

11：10-11：30 赵国庆，中国人民大学经济学院

11：30-11：50 田茂再，中国人民大学统计学院

11：50-13：30 午餐    地点：中区食堂三层餐厅

13：30-13：45 赵作权，中国科学院科技政策与管理科学研究所

13：45-14：00 戴平生； 陈建宝，厦门大学计划统计学院

14：00-14：15 张军舰，北京工业大学应用数理学院

14：15-14：30 田玉斌，北京理工大学 理学院

14：30-14：45 刘中华，中国人民大学统计学院

14：45-15：00 栾文英，山东经济学院

15：00-15：30 茶歇（明德主楼4层）

15：30-17：00 戴世光教授百年诞辰学术研讨会

6月22号 分会场2 (明德主楼0405教室)

8：10-8：30 Chunming Zhang，Department of Statistics, University of Wisconsin, Madison

8：30-8：50 荆柄义，香港科技大学数学系

8：50-9：10 谢邦昌，辅仁大学统计资讯学系

9：10-9：30 王学仁，云南大学数学与统计学院统计系

9：30-9：50 郑纪伦，中央研究院统计科学研究所

9：50-10:10

10:10-10:30 刘金山，华南农业大学理学院统计系

10：30-10：50 吕晓玲，中国人民大学统计学院

10：50-11：10 李竹渝，四川大学数学学院

11：10-11：30 王华；金勇进，厦门大学  中国人民大学统计学院

11：30-13：30

13：30-13：45 唐启义，浙江大学农业与生物技术学院

13：45-14：00 林海明，广东商学院经济贸易与统计学院

14：00-14：15 聂巧平 冯蕾，天津商业大学经济学院；国家统计局统计研究所

14：15-14：30 侯志强，北方工业大学

14：30-14：45 戴平生； 曾五一，厦门大学计划统计学院

14：45-15：00 孙慧钧，东北财经大学统计学院

15：00-15：30 茶歇（明德主楼4层）

15：30-17：00 戴世光教授百年诞辰学术研讨会

6月22号 分会场3 （明德主楼0406教室）

8：10-8：30 Huiyu Zhang，Reserving Actuary, Cuna Mutual Insurance Group

8：30-8：50 刘乐平，天津财经大学 统计学院

8：50-9：10 孟生旺，中国人民大学统计学院

9：10-9：30 张连增，南开大学风险管理与保险学系

9：30-9：50 王传玉； 申文康，安徽工程科技学院 应用数理系

9：50-10：10 茶歇（明德主楼4层）

10：10-10：30 黄向阳，中国人民大学统计学院

10：30-10：50 王晓军 钱珍，中国人民大学统计学院

10：50-11：10 石庆焱，国家统计局统计科学研究所

11：10-11：30 柳会珍，北京化工大学

11：30-11：50 韩海波，兰州商学院统计学院

11：50-13：30

13：30-13：45 张建标 王传玉，安徽工程科技学院应用数理系

13：45-14：00 刘潭秋；孙湘海，长沙理工大学经济与管理学院

14：00-14：15 陈昊，江苏电力公司南京供电公司

14：15-14：30 蔡正高，王晓军，中国人民大学统计学院

14：30-14：45 王博，中国人民大学信息学院

14：45-15：00 尹伟，南开大学风险管理与保险学系

15：00－15：15 黄媛，中国人民大学统计学院

15：15－15：30 茶歇（明德主楼4层）

15：30-17；00 戴世光教授百年诞辰学术研讨会

6月22号 分会场4 （明德主楼0407教室）

8：10-8：30 Haibo Zhou，the School of Public Health, the Center for Environmental Medicine, Asthma and Lung Biology

Environmental Health Studies

8：30-8：50 刘韫宁，首都医科大学公共卫生与家庭医学学院

8：50-9：10 施红英，温州医学院环境与公共卫生学院

9：10-9：30 李赞华，北京中医药大学循证医学中心

9：30-9：50 郭剑，津市塘沽区疾病预防与控制中心

9：50-10：10 王媛，天津医科大学卫生统计学教研室

10：10-10：30 茶歇 （明德主楼4层）

10：30-10：50 林筱文，福州大学管理学院统计系

10：50-11：10 斯琴，内蒙古财经学院统计系

11：10-11：30 季迎春； 陶磊，云南省思茅财经学校

11：30-11：50 侯瑜，东北财经大学 经济与社会发展研究院

11：50-13：30  午餐  地点：中区食堂三层餐厅

13：30-13：45 郭志伟，东北财经大学统计学院

13：45-14：00 胡恩生，华侨大学商学院经济系

14：00-14：15 王吉培，.西南财经大学统计学院

14：15-14：30 许晓娟，中国人民大学统计学院

14：30-14：45 顾玲，河北大学经济学院

14：45-15：00 王丹丹，中国人民大学 统计学院

15：00－15：15 刘崇光，中国人民大学统计学院

15：15-15：30 茶歇（明德主楼4层）

15：30-17；00 戴世光教授百年诞辰学术研讨会

6月22号 分会场5 （明德主楼0408教室）

8：10-8：30 余芳东，国家统计局

8：30-8：50 白先春，南京财经大学统计系

8：50-9：10 范秀荣，贺本岚，重庆工商大学数学与统计学院

9：10-9：30 杨京英，国家统计局统计科学研究所

9：30-9：50 罗乐勤，吴燕华，厦门大学计划统计系

9：50-10：10 茶歇（明德主楼4层）

10：10-10：30 刘保珺，关欣，陈平，天津财经大学；中国工商银行北京分行

10：30-10：50 汪彩玲，陈相成，厦门大学经济学院,

10：50-11：10 李武选，长安大学经济与管理学院

11：10-11：30 李金昌，浙江工商大学

11：50-13：30

13：30-13：45 孔建新，暨南大学工业工程管理在职研究生

13：45-14：00 张宝军，中央财经大学统计学院

14：00-14：15 谢润椿，暨南大学经济学院统计学系

14：15-14：30 何强，中央财经大学统计学院

14：30-14：45 朱婷，天津财经大学数量经济学

15：45-15：30 茶歇（明德主楼4层）

15：30-17；00 戴世光教授百年诞辰学术研讨会

（中央研究院統計科學研究所，台北南港）

A Unified Theory for GMM Estimation in Panel Data

Models with Measurement Error

Jun Shao

Abstract：Panel data allow correction for measurement error without using external information. Griliches and Hausman (1986) proposed using the generalized method of moments (GMM) or optimal weighting to efficiently combine instrumental variable (IV) estimators. Wansbeek (2001) applied GMM based on moment conditions expressed in the form of the Kronecker product. This paper studies some issues that are not addressed or not fully addressed by Griliches and Hausman (1986) or Wansbeek (2001) but are crucial to applications of these two approaches, these include how to choose instruments, what is the optimal weighted IV estimator, how to explicitly construct GMM estimators, how to remove the redundancy of the moment conditions constructed by Wansbeek (2001), and the existence of optimal GMM estimators. We unify Griliches and Hausman's and Wansbeek's approaches by establishing their equivalence. We also consider models with exogenous regressors and models with nonclassical assumptions. We apply the methods in this paper to revisit a investment controversy, viz., whether financially constrained firms respond to internal funds such as cash flow more sensitively than financially unconstrained firms.

Statistical methods for multivariate failure time data

Jianwen Cai

(Department of Biostatistics, University of North Carolina)

Abstract: Multivariate failure time data arise in many contexts. Some examples are: in epidemiological cohort studies in which the ages of disease occurrence are recorded for members of families; in animal experiments where treatments are applied to samples of littermates; in clinical trials in which individual study subjects are followed for the occurrence of multiple events; or, in intervention trials involving group randomization.

A common feature of the data in these examples is that the failure times might be correlated.

Over the past few years, we have developed statistical methods for various practical situations involving correlated failure time data.

In this talk, I will give an overview of these developments. I will focus on three general areas: (1) semiparametric methods for making inferences on linear and nonlinear covariates effects;(2) variable selection; and (3) joint modeling of recurrent event and recurrent marker. Examples will be drawn from biomedical studies

The Theory and Practice on Monetary and Financial Statistics

－A case survey in Zambia －

Nan Zhang

Hiroshima Shudo University (Japan)

The Monetary and Financial Statistics Manual (MFSM) was made by International Monetary Fund (IMF) in 2000, and it is to offer guidelines for the presentation of monetary and financial statistics. In addition to their role in assisting in monetary policy formulation and monitoring, the statistics covered in this volume form a basis for the development of a statistical framework for assessing financial sector. And the MFSM is harmonized with the 1993 SNA. Because the MFSM focuses on stocks and flows for financial corporation’s sector, it may, for the most part, be seen as extending and elaborating on the 1993 SNA in this area.

This report documented the principal findings and recommendations of the monetary and financial statistics mission from the Statistics Department (STA) of the IMF that visited Lusaka 2008. The main objectives of the mission were to: (i) review progress made by the Bank of Zambia (BOZ) in implementing the recommendations of the April/May 2005 monetary and financial statistics mission; (ii) assist in expanding the institutional coverage of the depository corporations survey; (iii) initiate work on the collection of data from other financial corporations and compilation of a financial corporation survey; (iv) verify the components of measures of the money supply and compilation of these monetary aggregates; and (v) discuss the units of central government used in classifying the deposits of government agencies at commercial banks.

The mission found that progress has been achieved in many areas, mainly in (i) timeliness and periodicity the BOZ submitted to STA, on a regular monthly basis, incorporating the accounts of all nonbank deposit-taking institutions and the compilation of the Form 1SR for the central bank’s accounts. And (ii) the compilation of the Form 2SR for the other depository corporations’ accounts, based on the recording system. Holdings of government securities by commercial banks reported. On the other hand, the implementation of some recommendation hasn’t been done, and the implementation recommendation has been slow. One important recommendation that had not been adopted was about collecting infrastructural data for recording of commercial banks.

Applications of Biostatistics in the Pharmaceutical Industry

William Wubao Wang, Ph.D

(Department of Biostatistics and Research Decision Sciences (BARDS)-China Operation)

Merck Research Laboratories

Merck & Co, Inc

Abstract: The growing trend of global clinical drug development demands increasing number of biometrics-related professionals (biostatisticians, clinical database administrator and clinical programmers) across the globe.  This trend is most recently reflected in the establishment of research and development operations in China and India by world's major pharmaceutical companies.

In this talk, we will provide an overview of the application of statistics and the role of clinical statisticians in the development of drug/vaccine products. We will discuss some recent trend in clinical study designs and analyses.  The Rotavirus Efficacy and Safety Trial (REST, n~72,000) will be used to illustrate some of these considerations (Vesikari et al. 2006, NEJM, 354(1): 23-33).

On principal components and regression: A statistical explanation of a natural phenomenon

Bing Li

(Professor of Statistics, Department of Statistics, Pennsylvania State University)

(joint work with Andreas Artemiou)

Abstract: In this talk we give a probabilistic explanation of a phenomenon that is frequently observed but whose reason is not well understood. That is, in a regression setting, the response (Y) is often highly correlated with the leading principal components of the predictor (X) even though there seems no logical reason for this connection. This phenomenon has long been noticed and discussed in the literature, and  has received renewed interest recently because of the need for regressing Y on  X of very high dimension, often with comparatively few sampling units, in which case it seems natural to regress on the first few principal components of X.

This work stems from a discussion of a recent paper by Cook (2007) which, along with other developments, described a historical debate surrounding, and current interest in, this phenomenon.

Learning a neighbor structure of a target in a causal network

Zhi Geng, You Zhou, Changchang Wang and Jianxin Yin

(School of Mathematical Sciences, Peking University, Beijing 100871, China)

Abstract: In causal discovery, a key issue is to discover causes of a target feature of interest. From observational studies, it is difficult to discover causes and effects of the target from a large number of observed features and especially to distinguish causes from effects. Discovering causal structures and further distinguishing causes from effects of a target are useful not only for prediction in the cases with external interventions, but also they are valuable for studying causal mechanisms, making decision and evaluating treatment effects. It is not easy to discover the parent nodes of a target in a large causal network. Although there are many structural learning approaches for discovering a global network, it is well known that learning a global network in an NP-Hard problem. If we are only interested in the neighbor of a target, it is inefficient and unnecessary to learn a global network.

Given a target variable of interest, we try to discover only the neighbor structure of the target. We propose in this paper two partial orientation and local structural learning (POLSL) approaches, Local-Graph and PCD-by-PCD. In the POLSL approaches, we locally discovery the edges connected to the target and only try to orient these edges so that we can distinguish the parents from the children of the target. We can theoretically show that the approach can correctly obtain the edges connected to the target and their orientations. The POLSL approaches can greatly reduce computational complexity of structural learning, and their statistical test is more powerful than a global learning approach.

Case Deletion, Replacement and Mean-shift Model

for Diagnostics in Linear Mixed Models

Lei Shi

(Statistics and Mathematics School, Yunnan University of Finance and Economics, Kunming, 650221, PRC)

Gemai Chen

(Department of Mathematics and Statistics, University of Calgary, AB, T2N 1N4, Canada)

Abstract: Case deletion, replacement and mean-shift model are frequently used in the detection of influential observations and outliers. In the general linear model with known covariance matrix, it is known these three techniques lead to the same results for the update formulae of the regression coefficients estimation. However if the covariance matrix is indexed by some unknown parameters which have to be estimated from the data set, the situation will be different. This paper study this issue in linear mixed model in which the parameter estimation are obtained iteratively. We propose several identities of case deletion method to derive and simplify the diagnostics for the estimation of parameters in covariance matrix and investigate the equivalence and non equivalence among three techniques. A example show that the misuse of replacement or mean-shift model for deletion diagnostics will lead to incorrect results.

Keywords: Case deletion, replacement, mean-shift model, diagnostics, influential observations.

Measurement of Real Exchange Rate Misalignment in China 1978-2007

Mustafa mohamed abdalla (B.Sc., M.Sc., Ph.D.)

（assistant professor in economics department of economics

faculty of economic and social studies university of khartoum

p o box 321  tel: 794923 mobile: 0918206239）

Abstract: The research is empirical and analytical in nature, methods of behavioural equilibrium exchange rate as well as purchasing power parity PPP, Capital enhanced equilibrium exchange rate and fundamental equilibrium exchange rate will be maniplualte to measure China RMB over/undervaluation.

QUOTIENT CORRELATION: A SAMPLE BASED ALTERNATIVE TO PEARSON'S CORRELATION

Zhengjun Zhang,

(University of Wisconsin)

Abstract: The quotient correlation is defined here as an alternative to Pearson's correlation that is more intuitive and flexible in cases where the tail behavior of data is important. It measures nonlinear dependence where the regular correlation coefficient is generally not applicable. One of its most useful features is a test statistic that has high power when testing nonlinear dependence in cases where the Fisher's $Z$-transformation test may fail to reach a right conclusion. Unlike most asymptotic test statistics, which are either normal or $\chi2$, this test statistic has a limiting gamma distribution (henceforth, the gamma test statistic). More than the common usages of correlation, the quotient correlation can easily and intuitively be adjusted to values at tails. This adjustment generates two new concept -- the tail quotient correlation and the tail independence test statistics, which are also gamma statistics. Due to the fact that there is no analogue of the correlation coefficient in extreme value theory, and there does not exist an efficient tail independence test statistic, these two new concepts may open up a new field of study. In  addition, an alternative to Spearman's rank correlation, a rank based quotient correlation, is also defined. The advantages of using these new concepts are illustrated with simulated data and real data analysis of internet traffic and asset returns.

A general adaptive L2 penalty method

Xiangrong Yin*

(Department of Statistics, University of Georgia, 204 Statistics Building, Athens, GA 30602)

Abstract: In this talk, we propose a general adaptive L2 penalty method. We show that it is a unfied method of adaptive lasso, adaptive ridge and adaptive elastic net penalties, making it a data-driven approach. We suggest new algorithms, providing important alternatives to the respective existing algorithms. Simulations and data analysis confirm the usefulness o our new approach.

• 2018.04.15

提交报告截止日期

• 2018.04.30

会议报名截止日期

• 2018.04.30

教师培训报名截止日期

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