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作者：Saha, Abhijoy; Bharath, Karthik; Kurtek, Sebastian
作者单位：University System of Ohio; Ohio State University; University of Nottingham
摘要：We propose a novel Riemannian geometric framework for variational inference in Bayesian models based on the nonparametric Fisher-Rao metric on the manifold of probability density functions. Under the square-root density representation, the manifold can be identified with the positive orthant of the unit hypersphere in , and the Fisher-Rao metric reduces to the standard metric. Exploiting such a Riemannian structure, we formulate the task of approximating the posterior distribution as a variati...
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作者：Zhao, Hui; Wu, Qiwei; Li, Gang; Sun, Jianguo
作者单位：Zhongnan University of Economics & Law; University of Missouri System; University of Missouri Columbia; University of California System; University of California Los Angeles
摘要：The simultaneous estimation and variable selection for Cox model has been discussed by several authors when one observes right-censored failure time data. However, there does not seem to exist an established procedure for interval-censored data, a more general and complex type of failure time data, except two parametric procedures. To address this, we propose a broken adaptive ridge (BAR) regression procedure that combines the strengths of the quadratic regularization and the adaptive weighted...
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作者：Cook, Richard J.
作者单位：University of Waterloo
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作者：Chen, Ming
作者单位：Amazon.com
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作者：Li, Kathleen T.
作者单位：University of Texas System; University of Texas Austin
摘要：The synthetic control (SC) method, a powerful tool for estimating average treatment effects (ATE), is increasingly popular in fields such as statistics, economics, political science, and marketing. The SC is particularly suitable for estimating ATE with a single (or a few) treated unit(s), a fixed number of control units, and large pre and post-treatment periods (which we refer as long panels). To date, there has been no formal inference theory for SC ATE estimator with long panels under gener...
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作者：Lila, Eardi; Aston, John A. D.
作者单位：University of Cambridge; University of Cambridge
摘要：In functional data analysis, data are commonly assumed to be smooth functions on a fixed interval of the real line. In this work, we introduce a comprehensive framework for the analysis of functional data, whose domain is a two-dimensional manifold and the domain itself is subject to variability from sample to sample. We formulate a statistical model for such data, here called functions on surfaces, which enables a joint representation of the geometric and functional aspects, and propose an as...
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作者：Xia, Yin; Li, Lexin; Lockhart, Samuel N.; Jagust, William J.
作者单位：Fudan University; University of California System; University of California Berkeley; Wake Forest University; University of California System; University of California Berkeley; United States Department of Energy (DOE); Lawrence Berkeley National Laboratory; University of California System; University of California Berkeley
摘要：Multimodal integrative analysis fuses different types of data collected on the same set of experimental subjects. It is becoming a norm in many branches of scientific research, such as multi-omics and multimodal neuroimaging analysis. In this article, we address the problem of simultaneous covariance inference of associations between multiple modalities, which is of a vital interest in multimodal integrative analysis. Recognizing that there are few readily available solutions in the literature...
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作者：Overstall, Antony M.; Woods, David C.; Parker, Ben M.
作者单位：University of Southampton; University of West London
摘要：Bayesian optimal design is considered for experiments where the response distribution depends on the solution to a system of nonlinear ordinary differential equations. The motivation is an experiment to estimate parameters in the equations governing the transport of amino acids through cell membranes in human placentas. Decision-theoretic Bayesian design of experiments for such nonlinear models is conceptually very attractive, allowing the formal incorporation of prior knowledge to overcome th...
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作者：Chernozhukov, Victor; Fernandez-Val, Ivan; Melly, Blaise; Wuthrich, Kaspar
作者单位：Massachusetts Institute of Technology (MIT); Boston University; University of Bern; University of California System; University of California San Diego
摘要：Quantile and quantile effect (QE) functions are important tools for descriptive and causal analysis due to their natural and intuitive interpretation. Existing inference methods for these functions do not apply to discrete random variables. This article offers a simple, practical construction of simultaneous confidence bands for quantile and QE functions of possibly discrete random variables. It is based on a natural transformation of simultaneous confidence bands for distribution functions, w...
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作者：Corradi, Valentina; Distaso, Walter; Fernandes, Marcelo
作者单位：University of Surrey; Imperial College London; Getulio Vargas Foundation
摘要：This article develops statistical tools for testing conditional independence among the jump components of the daily quadratic variation, which we estimate using intraday data. To avoid sequential bias distortion, we do not pretest for the presence of jumps. If the null is true, our test statistic based on daily integrated jumps weakly converges to a Gaussian random variable if both assets have jumps. If instead at least one asset has no jumps, then the statistic approaches zero in probability....
