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作者：Newton, Michael A.; Chung, Lisa M.
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：Discrete mixture models provide a well-known basis for effective clustering algorithms, although technical challenges have limited their scope. In the context of gene-expression data analysis, a model is presented that mixes over a finite catalog of structures, each one representing equality and inequality constraints among latent expected values. Computations depend on the probability that independent gamma-distributed variables attain each of their possible orderings. Each ordering event is ...
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作者：Jing, Bing-Yi; Pan, Guangming; Shao, Qi-Man; Zhou, Wang
作者单位：Hong Kong University of Science & Technology; Nanyang Technological University; National University of Singapore
摘要：The density function of the limiting spectral distribution of general sample covariance matrices is usually unknown. We propose to use kernel estimators which are proved to be consistent. A simulation study is also conducted to show the performance of the estimators.
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作者：Bathia, Neil; Yao, Qiwei; Ziegelmann, Flavio
作者单位：University of London; London School Economics & Political Science; Universidade Federal do Rio Grande do Sul
摘要：The curve time series framework provides a convenient vehicle to accommodate some nonstationary features into a stationary setup. We propose a new method to identify the dimensionality of curve time series based on the dynamical dependence across different curves. The practical implementation of our method boils down to an eigenanalysis of a finite-dimensional matrix. Furthermore, the determination of the dimensionality is equivalent to the identification of the nonzero eigenvalues of the matr...
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作者：Yuan, Ming; Cai, T. Tony
作者单位：University System of Georgia; Georgia Institute of Technology; University of Pennsylvania
摘要：We study in this paper a smoothness regularization method for functional linear regression and provide a unified treatment for both the prediction and estimation problems. By developing a tool on simultaneous diagonalization of two positive definite kernels, we obtain shaper results on the minimax rates of convergence and show that smoothness regularized estimators achieve the optimal rates of convergence for both prediction and estimation under conditions weaker than those for the functional ...
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作者：Liang, Hua; Liu, Xiang; Li, Runze; Tsai, Chih-Ling
作者单位：University of Rochester; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; University of California System; University of California Davis
摘要：In partially linear single-index models, we obtain the semiparametrically efficient profile least-squares estimators of regression coefficients. We also employ the smoothly clipped absolute deviation penalty (SCAD) approach to simultaneously select variables and estimate regression coefficients. We show that the resulting SCAD estimators are consistent and possess the oracle property. Subsequently, we demonstrate that a proposed tuning parameter selector, BIC, identifies the true model consist...
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作者：Chan, Ngai Hang; Ling, Shiqing
作者单位：Chinese University of Hong Kong; Hong Kong University of Science & Technology
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作者：Goeman, Jelle J.; Solari, Aldo
作者单位：Leiden University; Leiden University Medical Center (LUMC); Leiden University - Excl LUMC; University of Padua
摘要：Closed testing and partitioning are recognized as fundamental principles of familywise error control. In this paper, we argue that sequential rejection can be considered equally fundamental as a general principle of multiple testing. We present a general sequentially rejective multiple testing procedure and show that many well-known familywise error controlling methods can be constructed as special cases of this procedure, among which are the procedures of Holm, Shaffer and Hochberg, parallel ...
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作者：Fan, Jianqing; Song, Rui
作者单位：Princeton University; Colorado State University System; Colorado State University Fort Collins
摘要：Ultrahigh-dimensional variable selection plays an increasingly important role in contemporary scientific discoveries and statistical research. Among others, Fan and Lv [J. R. Stat. Soc. Ser. B Stat. Methodol. 70 (2008) 849-911] propose an independent screening framework by ranking the marginal correlations. They showed that the correlation ranking procedure possesses a sure independence screening property within the context of the linear model with Gaussian covariates and responses. In this pa...
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作者：El Karoui, Noureddine
作者单位：University of California System; University of California Berkeley
摘要：We first study the properties of solutions of quadratic programs with linear equality constraints whose parameters are estimated from data in the high-dimensional setting where p, the number of variables in the problem, is of the same order of magnitude as n, the number of observations used to estimate the parameters. The Markowitz problem in Finance is a subcase of our study. Assuming normality and independence of the observations we relate the efficient frontier computed empirically to the t...
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作者：Hallin, Marc; Paindaveine, Davy; Verdebout, Thomas
作者单位：Universite Libre de Bruxelles; Universite Libre de Bruxelles; Universite de Lille
摘要：This paper provides parametric and rank-based optimal tests for eigenvectors and eigenvalues of covariance or scatter matrices in elliptical families. The parametric tests extend the Gaussian likelihood ratio tests of Anderson (1963) and their pseudo-Gaussian robustifications by Davis (1977) and Tyler (1981, 1983). The rank-based tests address a much broader class of problems, where covariance matrices need not exist and principal components are associated with more general scatter matrices. T...
