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作者：Dette, Holger; Kokot, Kevin
作者单位：Ruhr University Bochum
摘要：We study the problem of testing equivalence of functional parameters, such as the mean or the variance function, in the two-sample functional data setting. In contrast to previous work where the functional problem is reduced to a multiple testing problem for the equivalence of scalar data by comparing the functions at each point, our approach is based on an estimate of a distance measuring the maximum deviation between the two functional parameters. Equivalence is claimed if the estimate for t...
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作者：Clarte, Gregoire; Robert, Christian P.; Ryder, Robin J.; Stoehr, Julien
作者单位：Universite PSL; Universite Paris-Dauphine
摘要：Approximate Bayesian computation methods are useful for generative models with intractable likelihoods. These methods are, however, sensitive to the dimension of the parameter space, requiring exponentially increasing resources as this dimension grows. To tackle this difficulty we explore a Gibbs version of the approximate Bayesian computation approach that runs component-wise approximate Bayesian computation steps aimed at the corresponding conditional posterior distributions, and based on su...
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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
摘要：Advances in digital technology and wearables have made it possible to deliver behavioural mobile health interventions to individuals in their everyday lives. Micro-randomized trials are increasingly used to provide data to inform the construction of these interventions. In a micro-randomized trial, each individual is repeatedly randomized among multiple intervention options, often hundreds or even thousands of times over the course of the trial. The work reported in this article is motivated b...
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作者：Garside, K.; Gjoka, A.; Henderson, R.; Johnson, H.; Makarenko, I
作者单位：Newcastle University - UK
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作者：Zhang, Y.; Laber, E. B.
作者单位：University of Rhode Island; Duke University
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作者：Na, S.; Kolar, M.; Koyejo, O.
作者单位：University of Chicago; University of Chicago; University of Illinois System; University of Illinois Urbana-Champaign
摘要：Differential graphical models are designed to represent the difference between the conditional dependence structures of two groups, and thus are of particular interest for scientific investigations. Motivated by modern applications, this manuscript considers an extended setting where each group is generated by a latent variable Gaussian graphical model. Due to the existence of latent factors, the differential network is decomposed into sparse and low-rank components, both of which are symmetri...
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作者：Sugasawa, S.
作者单位：University of Tokyo
摘要：A two-stage normal hierarchical model called the Fay-Herriot model and the empirical Bayes estimator are widely used to obtain indirect and model-based estimates of means in small areas. However, the performance of the empirical Bayes estimator can be poor when the assumed normal distribution is misspecified. This article presents a simple modification that makes use of density power divergence and proposes a new robust empirical Bayes small area estimator. The mean squared error and estimated...
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作者：Miles, C. H.; Shpitser, I; Kanki, P.; Meloni, S.; Tchetgen, E. J. Tchetgen
作者单位：Columbia University; Johns Hopkins University; Harvard University; Harvard T.H. Chan School of Public Health; University of Pennsylvania
摘要：Path-specific effects constitute a broad class of mediated effects from an exposure to an outcome via one or more causal pathways along a set of intermediate variables. Most of the literature concerning estimation of mediated effects has focused on parametric models, with stringent assumptions regarding unmeasured confounding. We consider semiparametric inference of a path-specific effect when these assumptions are relaxed. In particular, we develop a suite of semiparametric estimators for the...
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作者：Zhang, Han; Deng, Lu; Schiffman, Mark; Qin, Jing; Yu, Kai
作者单位：National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); NIH National Cancer Institute- Division of Cancer Epidemiology & Genetics; National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID)
摘要：Meta-analysis has become a powerful tool for improving inference by gathering evidence from multiple sources. It pools summary-level data from different studies to improve estimation efficiency with the assumption that all participating studies are analysed under the same statistical model. It is challenging to integrate external summary data calculated from different models with a newly conducted internal study in which individual-level data are collected. We develop a novel statistical infer...
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作者：Fong, E.; Holmes, C. C.
作者单位：University of Oxford
摘要：In Bayesian statistics, the marginal likelihood, also known as the evidence, is used to evaluate model fit as it quantifies the joint probability of the data under the prior. In contrast, non-Bayesian models are typically compared using cross-validation on held-out data, either through k-fold partitioning or leave-p-out subsampling. We show that the marginal likelihood is formally equivalent to exhaustive leave-p-out cross-validation averaged over all values of p and all held-out test sets whe...
