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Eigen techniques such as empirical orthogonal function (EOF) or coupled pattern (CP) analysis have been frequently used for detecting patterns in multivariate climatological data sets. Recently, stati...
As continuous glucose monitors (CGMs) are used increasingly by diabetic patients, new and intuitive tools are needed to help patients and their physicians use these streams of data to improve blood gl...
The standard approach to rank the performance of several classifiers for a given classification problem is via an independent labeled validation dataset. However, in various applications only unlabele...
We study the problem of high-dimensional regression when there may be interacting vari-ables. We introduce a new idea called Backtracking, that can be incorporated into many existing high-dimensional ...
This paper describes a novel approach to changepoint detection when the observed high-dimensional data may have missing elements. The performance of classical methods for changepoint detection typical...
We study the problem of two-sample comparisons with categorical data when the contingency table is sparsely populated. Classical methods, such as the Pearson's Chi-square test and the deviance test, ...
This paper investigates the property of the penalized estimating equations when both the mean and association structures are modelled. To select variables for the mean and association structures seque...
A very important topic in systems biology is developing statistical methods that automatically find causal relations in gene regulatory net-works with no prior knowledge of causal connectivity. Many m...
Sparse coding has been popularly used as an effective data represen-tation method in various applications, such as computer vision, medical imaging and bioinformatics, etc. However, the conventional s...
Many man-made and natural phenomena, including the intensity of earthquakes, population of cities, and size of international wars, are believed to follow power-law distributions. The accurate identifi...
In many applications, it is of interest to assess the dependence structure in multivariate longitudinal data. Discovering such dependence is challenging due to the dimensionality involved. By concate...
In the context of multilevel longitudinal data, where sample units are collected in clusters, an important aspect that should be accounted for is the unobserved heterogeneity between sample units and ...
Many biological characteristics of evolutionary inter-est are not scalar variables but continuous functions.Here we use phylogenetic Gaussian process regres-sion to model the evolution of simulated fu...
Nonlinear/non-Gaussian ltering has broad applications in many areas of life sciences where either the dynamic is nonlinear and/or the probability density function of un-certain state is non-Gaussian....
Freedman [Adv. in Appl. Math.40(2008) 180–193; Ann. Appl.Stat.2(2008) 176–196] critiqued ordinary least squares regression ad-justment of estimated treatment effects in randomized experiments,using Ne...

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