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作者：Liu, Yu; Ren, Zhao
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
摘要：The last decade has witnessed significant methodological and theoretical advances in estimating large precision matrices. In particular, there are scientific applications such as longitudinal data, meteorology and spectroscopy in which the ordering of the variables can be interpreted through a bandable structure on the Cholesky factor of the precision matrix. However, the minimax theory has still been largely unknown, as opposed to the well established minimax results over the corresponding ba...
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作者：Ding, Xiucai; Zhou, Zhou
作者单位：University of Toronto
摘要：We consider the estimation of and inference on precision matrices of a rich class of univariate locally stationary linear and nonlinear time series, assuming that only one realization of the time series is observed. Using a Cholesky decomposition technique, we show that the precision matrices can be directly estimated via a series of least squares linear regressions with smoothly time-varying coefficients. The method of sieves is utilized for the estimation and is shown to be optimally adaptiv...
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作者：Kohler, Michael; Langer, Sophie
作者单位：Technical University of Darmstadt
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作者：Schmidt-Hieber, Johannes
作者单位：University of Twente
摘要：Consider the multivariate nonparametric regression model. It is shown that estimators based on sparsely connected deep neural networks with ReLU activation function and properly chosen network architecture achieve the minimax rates of convergence (up to log n-factors) under a general composition assumption on the regression function. The framework includes many well-studied structural constraints such as (generalized) additive models. While there is a lot of flexibility in the network architec...
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作者：Kennedy, Edward H.; Balakrishnan, Sivaraman; G'Sell, Max
作者单位：Carnegie Mellon University
摘要：It is well known that, without restricting treatment effect heterogeneity, instrumental variable (IV) methods only identify local effects among compliers, that is, those subjects who take treatment only when encouraged by the IV. Local effects are controversial since they seem to only apply to an unidentified subgroup; this has led many to denounce these effects as having little policy relevance. However, we show that such pessimism is not always warranted: it can be possible to accurately pre...
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作者：Rockova, Veronika; Van der Pas, Stephanie
作者单位：University of Chicago; Leiden University - Excl LUMC; Leiden University
摘要：Since their inception in the 1980s, regression trees have been one of the more widely used nonparametric prediction methods. Tree-structured methods yield a histogram reconstruction of the regression surface, where the bins correspond to terminal nodes of recursive partitioning. Trees are powerful, yet susceptible to overfitting. Strategies against overfitting have traditionally relied on pruning greedily grown trees. The Bayesian framework offers an alternative remedy against overfitting thro...
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作者：Mourtada, Jaouad; Gaiffas, Stephane; Scornet, Erwan
作者单位：Institut Polytechnique de Paris; Ecole Polytechnique; Universite Paris Cite
摘要：Introduced by Breiman (Mach. Learn. 45 (2001) 5-32), Random Forests are widely used classification and regression algorithms. While being initially designed as batch algorithms, several variants have been proposed to handle online learning. One particular instance of such forests is the Mondrian forest (In Adv. Neural Inf. Process. Syst. (2014) 3140-3148; In Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AIS-TATS) (2016)), whose trees are built usin...
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作者：Meyer, Marco; Paparoditis, Efstathios; Kreiss, Jens-Peter
作者单位：Braunschweig University of Technology; University of Cyprus
摘要：Existing frequency domain methods for bootstrapping time series have a limited range. Essentially, these procedures cover the case of linear time series with independent innovations, and some even require the time series to be Gaussian. In this paper we propose a new frequency domain bootstrap method-the hybrid periodogram bootstrap (HPB)-which is consistent for a much wider range of stationary, even nonlinear, processes and which can be applied to a large class of periodogram-based statistics...
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作者：Zhilova, Mayya
作者单位：University System of Georgia; Georgia Institute of Technology
摘要：We study accuracy of bootstrap procedures for estimation of quantiles of a smooth function of a sum of independent sub-Gaussian random vectors. We establish higher-order approximation bounds with error terms depending on a sample size and a dimension explicitly. These results lead to improvements of accuracy of a weighted bootstrap procedure for general log-likelihood ratio statistics. The key element of our proofs of the bootstrap accuracy is a multivariate higher-order Berry-Esseen inequalit...
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作者：Patilea, Valentin; Van Keilegom, Ingrid
作者单位：Universite de Rennes; Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI); KU Leuven
摘要：In survival analysis it often happens that some subjects under study do not experience the event of interest; they are considered to be cured. The population is thus a mixture of two subpopulations, one of cured subjects and one of susceptible subjects. We propose a novel approach to estimate a mixture cure model when covariates are present and the lifetime is subject to random right censoring. We work with a parametric model for the cure proportion, while the conditional survival function of ...
