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作者：Nevo, Daniel; Lok, Judith J.; Spiegelman, Donna
作者单位：Tel Aviv University; Boston University; Yale University; Yale University
摘要：In Learn-As-you-GO (LAGO) adaptive studies, the intervention is a complex multicomponent package, and is adapted in stages during the study based on past outcome data. This design formalizes standard practice in public health intervention studies. An effective intervention package is sought, while minimizing intervention package cost. In LAGO study data, the interventions in later stages depend upon the outcomes in the previous stages, violating standard statistical theory. We develop an estim...
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作者：Di Benedetto, Giuseppe; Caron, Francois; Teh, Yee Whye
作者单位：University of Oxford
摘要：Many popular random partition models, such as the Chinese restaurant process and its two-parameter extension, fall in the class of exchangeable random partitions, and have found wide applicability in various fields. While the exchangeability assumption is sensible in many cases, it implies that the size of the clusters necessarily grows linearly with the sample size, and such feature may be undesirable for some applications. We present here a flexible class of nonexchangeable random partition ...
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作者：Hidalgo, Javier
作者单位：University of London; London School Economics & Political Science
摘要：The aim of the paper is to describe a bootstrap, contrary to the sieve boot-strap, valid under either long memory (LM) or short memory (SM) dependence. One of the reasons of the failure of the sieve bootstrap in our context is that under LM dependence, the sieve bootstrap may not be able to capture the true covariance structure of the original data. We also describe and examine the validity of the bootstrap scheme for the least squares estimator of the parameter in a regression model and for m...
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作者：Goeman, Jelle J.; Hemerik, Jesse; Solari, Aldo
作者单位：Leiden University; Leiden University Medical Center (LUMC); Leiden University - Excl LUMC; University of Oslo; Wageningen University & Research; University of Milano-Bicocca
摘要：We consider the class of all multiple testing methods controlling tail probabilities of the false discovery proportion, either for one random set or simultaneously for many such sets. This class encompasses methods controlling familywise error rate, generalized familywise error rate, false discovery exceedance, joint error rate, simultaneous control of all false discovery proportions, and others, as well as gene set testing in genomics and cluster inference in neuroimaging. We show that all su...
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作者：Huetter, Jan-Christian; Rigollet, Philippe
作者单位：Harvard University; Massachusetts Institute of Technology (MIT); Broad Institute; Massachusetts Institute of Technology (MIT)
摘要：Brenier's theorem is a cornerstone of optimal transport that guarantees the existence of an optimal transport map T between two probability distributions P and Q over R-d under certain regularity conditions. The main goal of this work is to establish the minimax estimation rates for such a transport map from data sampled from P and Q under additional smoothness assumptions on T. To achieve this goal, we develop an estimator based on the minimization of an empirical version of the semidual opti...
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作者：Feng, Oliver Y.; Guntuboyina, Adityanand; Kim, Arlene K. H.; Samworth, Richard J.
作者单位：University of Cambridge; University of California System; University of California Berkeley; Korea University
摘要：We study the adaptation properties of the multivariate log-concave maximum likelihood estimator over three subclasses of log-concave densities. The first consists of densities with polyhedral support whose logarithms are piece-wise affine. The complexity of such densities f can be measured in terms of the sum Gamma(f) of the numbers of facets of the subdomains in the polyhedral subdivision of the support induced by f. Given n independent observations from a d-dimensional log-concave density wi...
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作者：Hirshberg, David A.; Wager, Stefan
作者单位：Stanford University
摘要：Many statistical estimands can expressed as continuous linear functionals of a conditional expectation function. This includes the average treatment effect under unconfoundedness and generalizations for continuous-valued and personalized treatments. In this paper, we discuss a general approach to estimating such quantities: we begin with a simple plug-in estimator based on an estimate of the conditional expectation function, and then correct the plugin estimator by subtracting a minimax linear...
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作者：Jing, Bing-Yi; Li, Ting; Lyu, Zhongyuan; Xia, Dong
作者单位：Hong Kong University of Science & Technology; Hong Kong Polytechnic University
摘要：We study the problem of community detection in multilayer networks, where pairs of nodes can be related in multiple modalities. We introduce a general framework, that is, mixture multilayer stochastic block model (MMSBM), which includes many earlier models as special cases. We propose a tensor-based algorithm (TWIST) to reveal both global/local memberships of nodes, and memberships of layers. We show that the TWIST procedure can accurately detect the communities with small misclassification er...
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作者：Borgs, Christian; Chayes, Jennifer T.; Cohn, Henry; Ganguly, Shirshendu
作者单位：University of California System; University of California Berkeley; Microsoft
摘要：We study graphons as a nonparametric generalization of stochastic block models, and show how to obtain compactly represented estimators for sparse networks in this framework. In contrast to previous work, we relax the usual boundedness assumption for the generating graphon and instead assume only integrability, so that we can handle networks that have long tails in their degree distributions. We also relax the usual assumption that the graphon is defined on the unit interval, to allow latent p...
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作者：Eaton, Morris L.; George, Edward, I
作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Pennsylvania
摘要：When statistical decision theory was emerging as a promising new paradigm, Charles Stein was to play a major role in the development of minimax theory for invariant statistical problems. In some of his earliest work with Gil Hunt, he set out to prove that, in problems where invariant procedures have constant risk, any best invariant test would be minimax among all tests. Although finding it not quite true in general, this led to the legendary Hunt-Stein theorem, which established the result un...
