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作者：Barreiro-Ures, D.; Cao, R.; Francisco-Fernandez, M.; Hart, J. D.
作者单位：Universidade da Coruna; Texas A&M University System; Texas A&M University College Station
摘要：Hall & Robinson (2009) proposed and analysed the use of bagged cross-validation to choose the bandwidth of a kernel density estimator. They established that bagging greatly reduces the noise inherent in ordinary cross-validation, and hence leads to a more efficient bandwidth selector. The asymptotic theory of Hall & Robinson (2009) assumes that N, the number of bagged subsamples, is 8. We expand upon their theoretical results by allowing N to be finite, as it is in practice. Our results indica...
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作者：Solus, L.; Wang, Y.; Uhler, C.
作者单位：Royal Institute of Technology; Tsinghua University; Massachusetts Institute of Technology (MIT)
摘要：Directed acyclic graphical models are widely used to represent complex causal systems. Since the basic task of learning such a model from data is NP-hard, a standard approach is greedy search over the space of directed acyclic graphs or Markov equivalence classes of directed acyclic graphs. As the space of directed acyclic graphs on p nodes and the associated space of Markov equivalence classes are both much larger than the space of permutations, it is desirable to consider permutation-based g...
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作者：Garside, K.; Gjoka, A.; Henderson, R.; Johnson, H.; Makarenko, I
作者单位：Newcastle University - UK
摘要：Persistent homology is used to track the appearance and disappearance of features as we move through a nested sequence of topological spaces. Equating the nested sequence to a filtration and the appearance and disappearance of features to events, we show that simple event history methods can be used for the analysis of topological data. We propose a version of the well-known Nelson-Aalen cumulative hazard estimator for the comparison of topological features of random fields and for testing par...
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作者：Qian, Tianchen; Yoo, Hyesun; Klasnja, Predrag; Almirall, Daniel; Murphy, Susan A.
作者单位：University of California System; University of California Irvine; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; Harvard University
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作者：Jentsch, Carsten; Lee, Eun Ryung; Mammen, Enno
作者单位：Dortmund University of Technology; Sungkyunkwan University (SKKU); Ruprecht Karls University Heidelberg
摘要：We discuss Poisson reduced-rank models for low-dimensional summaries of high-dimensional Poisson vectors that allow inference on the location of individuals in a low-dimensional space. We show that under weak dependence conditions, which allow for certain correlations between the Poisson random variables, the locations can be consistently estimated using Poisson maximum likelihood estimation. Moreover, we develop consistent rules for determining the dimension of the location from the discrete ...
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作者：Chang, Jinyuan; Chen, Song Xi; Tang, Cheng Yong; Wu, Tong Tong
作者单位：Southwestern University of Finance & Economics - China; Peking University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University; University of Rochester
摘要：High-dimensional statistical inference with general estimating equations is challenging and remains little explored. We study two problems in the area: confidence set estimation for multiple components of the model parameters, and model specifications tests. First, we propose to construct a new set of estimating equations such that the impact from estimating the high-dimensional nuisance parameters becomes asymptotically negligible. The new construction enables us to estimate a valid confidenc...
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作者：Schmon, S. M.; Deligiannidis, G.; Doucet, A.; Pitt, M. K.
作者单位：University of Oxford; University of London; King's College London
摘要：The pseudo-marginal algorithm is a variant of the Metropolis-Hastings algorithm which samples asymptotically from a probability distribution when it is only possible to estimate unbiasedly an unnormalized version of its density. Practically, one has to trade off the computational resources used to obtain this estimator against the asymptotic variances of the ergodic averages obtained by the pseudo-marginal algorithm. Recent works on optimizing this trade-off rely on some strong assumptions, wh...
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作者：Ma, Rong; Cai, T. Tony; Li, Hongzhe
作者单位：University of Pennsylvania; University of Pennsylvania
摘要：Motivated by the problem of estimating bacterial growth rates for genome assemblies from shotgun metagenomic data, we consider the permuted monotone matrix model Y = Theta Pi + Z where Y is an element of R-nxp is observed, Theta is an element of R-nxp an unknown approximately rank-one signal matrix with monotone rows, Pi is an element of R-pxp is an unknown permutation matrix, and Z is an element of R-nxp is the noise matrix. In this article we study estimation of the extreme values associated...
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作者：Amico, M.; Van Keilegom, I; Han, B.
作者单位：KU Leuven
摘要：Survival analysis relies on the hypothesis that, if the follow-up is long enough, the event of interest will eventually be observed for all observations. This assumption, however, is often not realistic. The survival data then contain a cure fraction. A common approach to modelling and analysing this type of data consists in using cure models. Two types of information can therefore be obtained: the survival at a given time and the cure status, both possibly modelled as a function of the covari...
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作者：Bogomolov, Marina; Peterson, Christine B.; Benjamini, Yoav; Sabatti, Chiara
作者单位：Technion Israel Institute of Technology; University of Texas System; UTMD Anderson Cancer Center; Tel Aviv University; Stanford University
摘要：We introduce a multiple testing procedure that controls global error rates at multiple levels of resolution. Conceptually, we frame this problem as the selection of hypotheses that are organized hierarchically in a tree structure. We describe a fast algorithm and prove that it controls relevant error rates given certain assumptions on the dependence between the p-values. Through simulations, we demonstrate that the proposed procedure provides the desired guarantees under a range of dependency ...
