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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...
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作者：Fan, Jianqing; Liao, Yuan
作者单位：Princeton University; University System of Maryland; University of Maryland College Park
摘要：Most papers on high-dimensional statistics are based on the assumption that none of the regressors are correlated with the regression error, namely, they are exogenous. Yet, endogeneity can arise incidentally from a large pool of regressors in a high-dimensional regression. This causes the inconsistency of the penalized least-squares method and possible false scientific discoveries. A necessary condition for model selection consistency of a general class of penalized regression methods is give...
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作者：Jacod, Jean; Todorov, Viktor
作者单位：Universite Paris Cite; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Sorbonne Universite; Northwestern University
摘要：We propose new nonparametric estimators of the integrated volatility of an Ito semimartingale observed at discrete times on a fixed time interval with mesh of the observation grid shrinking to zero. The proposed estimators achieve the optimal rate and variance of estimating integrated volatility even in the presence of infinite variation jumps when the latter are stochastic integrals with respect to locally stable Levy processes, that is, processes whose Levy measure around zero behaves like t...
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作者：Belloni, Alexandre; Chernozhukov, Victor; Wang, Lie
作者单位：Duke University; Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT)
摘要：We propose a self-tuning root Lasso method that simultaneously resolves three important practical problems in high-dimensional regression analysis, namely it handles the unknown scale, heteroscedasticity and (drastic) non-Gaussianity of the noise. In addition, our analysis allows for badly behaved designs, for example, perfectly collinear regressors, and generates sharp bounds even in extreme cases, such as the infinite variance case and the noiseless case, in contrast to Lasso. We establish v...
