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- Tailen Hsing, Sanju Attoor, Edward R. Dougherty
- Machine Learning
- 2003

Gene-expression-based classifiers suffer from the small number of microarrays usually available for classifier design. Hence, one is confronted with the dual problem of designing a classifier and estimating its error with only a small sample. Permutation testing has been recommended to assess the dependency of a designed classifier on the specific data set.… (More)

- N. E. Savin, Sanford J. Grossman, Zhongquan Zhou, Tailen Hsing, Andrew W. Lo, P. M. Robinson +4 others
- 2006

- Tailen Hsing, Li-Yu Liu, Marcel Brun, Edward R. Dougherty
- Pattern Recognition
- 2005

Measuring the strength of dependence between two sets of random variables lies at the heart of many statistical problems, in particular, feature selection for pattern recognition. We believe that there are some basic desirable criteria for a measure of dependence not satisfied by many commonly employed measures, such as the correlation coefficient, Briefly… (More)

- Tailen Hsing, Wei Biao Wu
- 2003

A weighted U-statistic based on a random sample X 1 ,. .. , X n has the form U n = 1≤i,j≤n w i−j K(X i , X j) where K is fixed symmetric measurable function and the w i are symmetric weights. A large class of statistics can be expressed as weighted U-statistics or variations thereof. This paper establishes the asymptotic normality of U n when the sample… (More)

We investigate extreme dependence in a multivariate setting with special emphasis on financial applications. We introduce a new dependence function which allows us to capture the complete extreme dependence structure and present a nonparametric estimation procedure. The new dependence function is compared with existing measures including the spectral… (More)

- Tailen Hsing
- 2012

In the study of intrinsically stationary spatial processes, a new nonparametric vari-ogram estimator is proposed through its spectral representation. The methodology is based on estimation of the variogram's spectrum, here for the isotropic case, which is formulated in terms of solving a regularized inverse problem. We use quadratic programming to obtain… (More)

- A. R. Ganguly, T. Hsing, R. Katz, D. Erickson, G. Ostrouchov, T. Wilbanks +1 other
- 2005

Problem Statement: The ability to understand and eventually predict climate extremes and abrupt change is critical for science [1-2, 12-13, 16-17] and policy [17-20], and can help answer questions like the following: (a) Are heat waves or precipitation extremes likely to grow more intense in the next century? (b) Is an increase in Atlantic hurricane… (More)

- HAOBO REN, Tailen Hsing, Raymond J. Carroll, Suojin Wang, Qi Li, Simon J. Sheather +2 others
- 2005

The basic philosophy of Functional Data Analysis (FDA) is to think of the observed data functions as elements of a possibly infinite-dimensional function space. Most of the current research topics on FDA focus on advancing theoretical tools and extending existing multivariate techniques to accommodate the infinite-dimensional nature of data. This… (More)

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