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Tonghui(Tony) Wang:Statistical and machine learning data mining --Techniques for betterpredictive modeling and analysis of big data

日期:2018-06-29      来源:工商管理学院 科技处    [字体: ]

题 目:Statistical and machinelearning data mining --Techniques for better predictive modeling and analysisof big data

报告人:Tonghui (Tony) Wang教授 博士生导师

时 间:2018年7月3日(星期二)8:30--11:30

地 点:MBA小案例室

内 容:In this talk, several basicdata mining methods are introduced, together with CHAID based statisticalanalysis techniques for big data. Real data examples are given for illustrationof these techniques.

报告人简介:

Tonghui (Tony) Wang,Department ofMathematical Sciences,New Mexico State University, LasCruces.

Education

Dec.1992 Ph.D. in Statistics, University of Windsor, Canada. Aug. 1988: M. Sc. inStatistics, University of Windsor, Canada. Jan. 1982: B. Sc. in Mathematics,Northwest University, China.

ResearchInterests

(i)Multivariate linear modelsand distributions of quadratic forms with applications in growth curve models,multivariate analysis of variance models, and the class of skew distributionsincluding skew normal, skew elliptical distributions.

(ii)Statistics of random setswith applications in coarsening data and fuzzy data.

(iii)Probability models andstatistical methods in reliability.

(iv)Applications of themathematical and statistical modeling.

(v)Copulas and their associatedmeasures with applications.

(vi)Statisticalinference of stochastic dominance and poverty measures with appli-

cations.

(vii)Statistical change pointsmethods.

RefereedPublications

1.D. Tramow, T. Wang, and C. Wang, From a Sampling Precision Perspective, Skewness is aFriend and not an Enemy! Educational and Psychological Measure-ment (2018).DOI: 10.1177/0013164418764801

2.D.Tra mow, T. Wang, and C. Wang, Means and standard deviations, or locations andscales? That is the question! New Ideas in Psychology, 50, pp. 34-37 (2018)

3.W. Tian, B. Li, T. Wang,Remarks for the singular multivariate skew-normal distribution and itsquadratic forms, Statistics and Probability Letters, DOI10.1016/j.spl.2018.01.008,Jan. (2018).

4.X. Zhu, B. Li, M. Wu, and T.Wang, Plausibility regions on parameters of the skew normal distribution basedon inferential models in \Predictive Econometrics and Big Data" (V.Krennovich, S. Sriboonchitta, and N. Chakpitak Eds.), Springer-Verlag, NewYork, pp. 287-302(2018).

5.W. Tian, T. Wang, F. Wei, andF. Dai, Shape mixture models based on multivari-ate extended skew normaldistributions in \Predictive Econometrics and Big Data" (V. Krennovich, S.Sriboonchitta, and N. Chakpitak Eds.), Springer-Verlag, New York, pp.273-286(2018).

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