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作者：Pagui, E. C. Kenne; Salvan, A.; Sartori, N.
作者单位：University of Padua
摘要：For regular parametric problems, we show how median centring of the maximum likelihood estimate can be achieved by a simple modification of the score equation. For a scalar parameter of interest, the estimator is equivariant under interest-respecting reparameterizations and is third-order median unbiased. With a vector parameter of interest, componentwise equivariance and third-order median centring are obtained. Like the implicit method of Firth (1993) for bias reduction, the new method does ...
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作者：Srivastava, Sanvesh; Engelhardt, Barbara E.; Dunson, David B.
作者单位：University of Iowa; Princeton University; Duke University
摘要：Bayesian sparse factor models have proven useful for characterizing dependence in multivariate data, but scaling computation to large numbers of samples and dimensions is problematic. We propose expandable factor analysis for scalable inference in factor models when the number of factors is unknown. The method relies on a continuous shrinkage prior for efficient maximum a posteriori estimation of a low-rank and sparse loadings matrix. The structure of the prior leads to an estimation algorithm...
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作者：Linero, A. R.
作者单位：State University System of Florida; Florida State University
摘要：In longitudinal clinical trials, one often encounters missingness that is thought to be nonignorable. Such missingness introduces identifiability issues, resulting in causal effects being nonparametrically unidentified; it is then prudent to conduct a sensitivity analysis to assess how much of the inference is being driven by untestable assumptions needed to identify the effects of interest. We introduce a Bayesian nonparametric framework for conducting inference in the presence of nonignorabl...
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作者：Johnstone, I. M.; Nadler, B.
作者单位：Stanford University; Weizmann Institute of Science
摘要：Roy's largest root is a common test statistic in multivariate analysis, statistical signal processing and allied fields. Despite its ubiquity, provision of accurate and tractable approximations to its distribution under the alternative has been a longstanding open problem. Assuming Gaussian observations and a rank-one alternative, or concentrated noncentrality, we derive simple yet accurate approximations for the most common low-dimensional settings. These include signal detection in noise, mu...
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作者：Kosmidis, I.; Guolo, A.; Varin, C.
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作者：Chang, Jinyuan; Yao, Qiwei; Zhou, Wen
作者单位：Southwestern University of Finance & Economics - China; University of London; London School Economics & Political Science; Colorado State University System; Colorado State University Fort Collins
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作者：Wang, Linbo; Robins, James M.; Richardson, Thomas S.
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard T.H. Chan School of Public Health; University of Washington; University of Washington Seattle
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作者：Stalder, Odile; Asher, Alex; Liang, Liang; Carroll, Raymond J.; Ma, Yanyuan; Chatterjee, Nilanjan
作者单位：University of Bern; Texas A&M University System; Texas A&M University College Station; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Johns Hopkins University
摘要：Many methods have recently been proposed for efficient analysis of case-control studies of gene-environment interactions using a retrospective likelihood framework that exploits the natural assumption of gene-environment independence in the underlying population. However, for polygenic modelling of gene-environment interactions, which is a topic of increasing scientific interest, applications of retrospective methods have been limited due to a requirement in the literature for parametric model...
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作者：Zhang, Yuan; Levina, Elizaveta; Zhu, Ji
作者单位：University System of Ohio; Ohio State University; University of Michigan System; University of Michigan
摘要：The estimation of probabilities of network edges from the observed adjacency matrix has important applications to the prediction of missing links and to network denoising. It is usually addressed by estimating the graphon, a function that determines the matrix of edge probabilities, but this is ill-defined without strong assumptions on the network structure. Here we propose a novel computationally efficient method, based on neighbourhood smoothing, to estimate the expectation of the adjacency ...
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作者：Sherlock, Chris; Thiery, Alexandre H.; Lee, Anthony
作者单位：Lancaster University; National University of Singapore; University of Warwick
摘要：We consider a pseudo-marginal Metropolis-Hastings kernel P-m that is constructed using an average of m exchangeable random variables, and an analogous kernel P-s that averages s < m of these same random variables. Using an embedding technique to facilitate comparisons, we provide a lower bound for the asymptotic variance of any ergodic average associated with P-m in terms of the asymptotic variance of the corresponding ergodic average associated with P-s. We show that the bound is tight and di...
