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作者：Fan, Jianqing; Feng, Yang; Niu, Yue S.
作者单位：Princeton University; Columbia University; University of Arizona
摘要：Estimation of genewise variance arises from two important applications in microarray data analysis: selecting significantly differentially expressed genes and validation tests for normalization of microarray data. We approach the problem by introducing a two-way nonparametric model, which is an extension of the famous Neyman-Scott model and is applicable beyond microarray data. The problem itself poses interesting challenges because the number of nuisance parameters is proportional to the samp...
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作者：Scott, James G.; Berger, James O.
作者单位：University of Texas System; University of Texas Austin; Duke University
摘要：This paper studies the multiplicity-correction effect of standard Bayesian variable-selection priors in linear regression. Our first goal is to clarify when, and how, multiplicity correction happens automatically in Bayesian analysis, and to distinguish this correction from the Bayesian Ockham's-razor effect. Our second goal is to contrast empirical-Bayes and fully Bayesian approaches to variable selection through examples, theoretical results and simulations. Considerable differences between ...
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作者：El Karoui, Noureddine
作者单位：University of California System; University of California Berkeley
摘要：Kernel random matrices have attracted a lot of interest in recent years, from both practical and theoretical standpoints. Most of the theoretical work so far has focused on the case were the data is sampled from a low-dimensional structure. Very recently, the first results concerning kernel random matrices with high-dimensional input data were obtained, in a setting where the data was sampled from a genuinely high-dimensional structure-similar to standard assumptions in random matrix theory. I...
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作者：Rinaldo, Alessandro; Wasserman, Larry
作者单位：Carnegie Mellon University
摘要：We study generalized density-based clustering in which sharply defined clusters such as clusters on lower-dimensional manifolds are allowed. We show that accurate clustering is possible even in high dimensions. We propose two data-based methods for choosing the bandwidth and we study the stability properties of density clusters. We show that a simple graph-based algorithm successfully approximates the high density clusters.
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作者：Li, Yehua; Hsing, Tailen
作者单位：University System of Georgia; University of Georgia; University of Michigan System; University of Michigan
摘要：In this paper, we consider regression models with a Hilbert-space-valued predictor and a scalar response, where the response depends on the predictor only through a finite number of projections. The linear subspace spanned by these projections is called the effective dimension reduction (EDR) space. To determine the dimensionality of the EDR space, we focus on the leading principal component scores of the predictor, and propose two sequential chi(2) testing procedures under the assumption that...
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作者：Botev, Z. I.; Grotowski, J. F.; Kroese, D. P.
作者单位：University of Queensland
摘要：We present a new adaptive kernel density estimator based on linear diffusion processes. The proposed estimator builds on existing ideas for adaptive smoothing by incorporating information from a pilot density estimate. In addition, we propose a new plug-in bandwidth selection method that is free from the arbitrary normal reference rules used by existing methods. We present simulation examples in which the proposed approach outperforms existing methods in terms of accuracy and reliability.
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作者：Lee, Young Kyung; Mammen, Enno; Park, Byeong U.
作者单位：Kangwon National University; University of Mannheim; Seoul National University (SNU)
摘要：In this paper, we study the ordinary backfitting and smooth backfitting as methods of fitting additive quantile models. We show that these backfitting quantile estimators are asymptotically equivalent to the corresponding backfitting estimators of the additive components in a specially-designed additive mean regression model. This implies that the theoretical properties of the backfitting quantile estimators are not unlike those of backfitting mean regression estimators. We also assess the fin...
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作者：Hall, Peter; Miller, Hugh
作者单位：University of Melbourne
摘要：For better or for worse, rankings of institutions, such as universities, schools and hospitals, play an important role today in conveying information about relative performance. They inform policy decisions and budgets, and are often reported in the media. While overall rankings can vary markedly over relatively short time periods, it is not unusual to find that the ranks of a small number of highly performing institutions remain fixed, even when the data on which the rankings are based are ex...
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作者：Rosenbaum, Mathieu; Tsybakov, Alexandre B.
作者单位：Institut Polytechnique de Paris; Ecole Polytechnique; Institut Polytechnique de Paris; ENSAE Paris; Sorbonne Universite
摘要：We consider the model y = X theta* + xi, Z = X + Xi, where the random vector y is an element of R-n and the random n x p matrix Z are observed, the n x p matrix X is unknown, Xi is an n x p random noise matrix, xi is an element of R-n is a noise independent of Xi, and theta* is a vector of unknown parameters to be estimated. The matrix uncertainty is in the fact that X is observed with additive error. For dimensions p that can be much larger than the sample size n, we consider the estimation o...
