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作者：Geenens, Gery
作者单位：University of New South Wales Sydney
摘要：Kernel estimation of a probability density function supported on the unit interval has proved difficult, because of the well-known boundary bias issues a conventional kernel density estimator would necessarily face in this situation. Transforming the variable of interest into a variable whose density has unconstrained support, estimating that density, and obtaining an estimate of the density of the original variable through back-transformation, seems a natural idea to easily get rid of the bou...
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作者：Liu, Lan; Hudgens, Michael G.
作者单位：Harvard University; Harvard University; University of North Carolina; University of North Carolina Chapel Hill
摘要：Recently, there has been increasing interest in making causal inference when interference is possible. In the presence of interference, treatment may have several types of effects. In this article, we consider inference about such effects when the population consists of groups of individuals where interference is possible within groups but not between groups. A two-stage randomization design is assumed where in the first stage groups are randomized to different treatment allocation strategies ...
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作者：Panaretos, Victor M.; Pham, Tung; Yao, Zhigang
作者单位：Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
摘要：We revisit the problem of extending the notion of principal component analysis (PCA) to multivariate datasets that satisfy nonlinear constraints, therefore lying on Riemannian manifolds. Our aim is to determine curves on the manifold that retain their canonical interpretability as principal components, while at the same time being flexible enough to capture nongeodesic forms of variation. We introduce the concept of a principal flow, a curve on the manifold passing through the mean of the data...
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作者：Airoldi, Edoardo M.; Costa, Thiago; Bassetti, Federico; Leisen, Fabrizio; Guindani, Michele
作者单位：Harvard University; Harvard University; University of Pavia; University of Kent; University of Texas System; UTMD Anderson Cancer Center
摘要：Many popular Bayesian nonparametric priors can be characterized in terms of exchangeable species sampling sequences. However, in some applications, exchangeability may not be appropriate. We introduce a novel and probabilistically coherent family of nonexchangeable species sampling sequences characterized by a tractable predictive probability function with weights driven by a sequence of independent Beta random variables. We compare their theoretical clustering properties with those of the Dir...
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作者：Huang, Hui; Li, Yehua; Guan, Yongtao
作者单位：Peking University; Peking University; Iowa State University; University of Miami
摘要：In a cocaine dependence treatment study, we have paired binary longitudinal trajectories that record the cocaine use patterns of each patient before and after a treatment. To better understand the drug-using behaviors among the patients, we propose a general framework based on functional data analysis to jointly model and cluster these paired non-Gaussian longitudinal trajectories. Our approach assumes that the response variables follow distributions from the exponential family, with the canon...
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作者：Mueller, Peter; Quintana, Fernando
作者单位：University of Texas System; University of Texas Austin; Pontificia Universidad Catolica de Chile
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作者：Bar, Haim Y.; Booth, James G.; Wells, Martin T.
作者单位：University of Connecticut; Cornell University; Cornell University
摘要：We develop a novel approach for testing treatment effects in high-throughput data. Most previous works on this topic focused on testing for differences between the means, but recently it has been recognized that testing for differential variation is probably as important. We take it a step further, and introduce a bivariate model modeling strategy which accounts for both differential expression and differential variation. Our model-based approach, in which the differential mean and variance ar...
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作者：Pan, Guangming; Gao, Jiti; Yang, Yanrong
作者单位：Nanyang Technological University; Monash University
摘要：random vectors of length p in the form of a matrix, we develop a linear spectral statistic of the constructed matrix to test whether the n random vectors are independent or not. Specifically, the proposed statistic can also be applied to n random vectors, each of whose elements can be written as either a linear stationary process or a linear combination of independent random variables. The asymptotic distribution of the proposed test statistic is established for the case of 0 < lim(n ->infinit...
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作者：Claeskens, Gerda; Hubert, Mia; Slaets, Leen; Vakili, Kaveh
作者单位：KU Leuven; KU Leuven; European Organisation for Research & Treatment of Cancer
摘要：This article defines and studies a depth for multivariate functional data. By the multivariate nature and by including a weight function, it acknowledges important characteristics of functional data, namely differences in the amount of local amplitude, shape, and phase variation. We study both population and finite sample versions. The multivariate sample of curves may include warping functions, derivatives, and integrals of the original curves for a better overall representation of the functi...
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作者：Portier, Francois; Delyon, Bernard
作者单位：Universite Catholique Louvain; Universite de Rennes
摘要：To test if an unknown matrix M-0 has a given rank (null hypothesis noted H-0), we consider a statistic that is a squared distance between an estimator (M) over cap and the submanifold of fixed-rank matrix. Under H-0, this statistic converges to a weighted chi-squared distribution. We introduce the constrained bootstrap (CS bootstrap) to estimate the law of this statistic under H-0. An important point is that even if H-0 fails, the CS bootstrap reproduces the behavior of the statistic under H-0...
