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作者：Jirak, Moritz; Meister, Alexander; Reiss, Markus
作者单位：Humboldt University of Berlin; University of Rostock
摘要：We consider the model of nonregular nonparametric regression where smoothness constraints are imposed on the regression function f and the regression errors are assumed to decay with some sharpness level at their endpoints. The aim of this paper is to construct an adaptive estimator for the regression function f. In contrast to the standard model where local averaging is fruitful, the nonregular conditions require a substantial different treatment based on local extreme values. We study this m...
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作者：Genovese, Christopher R.; Perone-Pacifico, Marco; Verdinelli, Isabella; Wasserman, Larry
作者单位：Carnegie Mellon University; Sapienza University Rome
摘要：We study the problem of estimating the ridges of a density function. Ridge estimation is an extension of mode finding and is useful for understanding the structure of a density. It can also be used to find hidden structure in point cloud data. We show that, under mild regularity conditions, the ridges of the kernel density estimator consistently estimate the ridges of the true density. When the data are noisy measurements of a manifold, we show that the ridges are close and topologically simil...
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作者：Wang, Li; Xue, Lan; Qu, Annie; Liang, Hua
作者单位：University System of Georgia; University of Georgia; Oregon State University; University of Illinois System; University of Illinois Urbana-Champaign; George Washington University
摘要：We propose generalized additive partial linear models for complex data which allow one to capture nonlinear patterns of some covariates, in the presence of linear components. The proposed method improves estimation efficiency and increases statistical power for correlated data through incorporating the correlation information. A unique feature of the proposed method is its capability of handling model selection in cases where it is difficult to specify the likelihood function. We derive the qu...
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作者：Bai, Jushan; Li, Kunpeng
作者单位：Columbia University; Capital University of Economics & Business; Tsinghua University
摘要：This paper considers the maximum likelihood estimation of panel data models with interactive effects. Motivated by applications in economics and other social sciences, a notable feature of the model is that the explanatory variables are correlated with the unobserved effects. The usual within-group estimator is inconsistent. Existing methods for consistent estimation are either designed for panel data with short time periods or are less efficient. The maximum likelihood estimator has desirable...
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作者：Celisse, Alain
作者单位：Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Universite de Lille
摘要：We analyze the performance of cross-validation (CV) in the density estimation framework with two purposes: (i) risk estimation and (ii) model selection. The main focus is given to the so-called leave-p-out CV procedure (Lpo), where p denotes the cardinality of the test set. Closed-form expressions are settled for the Lpo estimator of the risk of projection estimators. These expressions provide a great improvement upon V-fold cross-validation in terms of variability and computational complexity...
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作者：Buehlmann, Peter; Meier, Lukas; van de Geer, Sara
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
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作者：Buja, A.; Brown, L.
作者单位：University of Pennsylvania
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作者：Chang, Chih-Hao; Huang, Hsin-Cheng; Ing, Ching-Kang
作者单位：National University Kaohsiung; Academia Sinica - Taiwan
摘要：Information criteria, such as Akaike's information criterion and Bayesian information criterion are often applied in model selection. However, their asymptotic behaviors for selecting geostatistical regression models have not been well studied, particularly under the fixed domain asymptotic framework with more and more data observed in a bounded fixed region. In this article, we study the generalized information criterion (GIC) for selecting geostatistical regression models under a more genera...
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作者：Chen, Xian; Ma, Zhi-Ming; Wang, Ying
作者单位：Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS
摘要：Genetic recombination is one of the most important mechanisms that can generate and maintain diversity, and recombination information plays an important role in population genetic studies. However, the phenomenon of recombination is extremely complex, and hence simulation methods are indispensable in the statistical inference of recombination. So far there are mainly two classes of simulation models practically in wide use: back-in-time models and spatially moving models. However, the statisti...
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作者：Aronow, Peter M.; Green, Donald P.; Lee, Donald K. K.
作者单位：Yale University; Columbia University; Yale University
摘要：We propose a consistent estimator of sharp bounds on the variance of the difference-in-means estimator in completely randomized experiments. Generalizing Robins [Stat. Med. 7 (1988) 773-785], our results resolve a well-known identification problem in causal inference posed by Neyman [Statist. Sci. 5 (1990) 465-472. Reprint of the original 1923 paper]. A practical implication of our results is that the upper bound estimator facilitates the asymptotically narrowest conservative Wald-type confide...
