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作者：Li, Jinzhou; Maathuis, Marloes H.
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
摘要：We propose a new method to learn the structure of a Gaussian graphical model with finite sample false discovery rate control. Our method builds on the knockoff framework of Barber and Candes for linear models. We extend their approach to the graphical model setting by using a local (node-based) and a global (graph-based) step: we construct knockoffs and feature statistics for each node locally, and then solve a global optimization problem to determine a threshold for each node. We then estimat...
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作者：Kim, Sungwook; Fay, Michael P.; Proschan, Michael A.
作者单位：National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID)
摘要：We introduce a new approach for creating pointwise confidence intervals for the distribution of event times for current status data. Existing methods are based on asymptotics. Our approach is based on binomial properties and motivates confidence intervals that are very simple to apply and are valid that is guarantee nominal coverage. Although these confidence intervals are necessarily conservative for small sample sizes, asymptotically their coverage rate approaches the nominal one. This binom...
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作者：Lee, Myoung-jae
作者单位：Korea University
摘要：Given an endogenous/confounded binary treatment D, a response Y with its potential versions (Y-0, Y-1) and covariates X, finding the treatment effect is difficult if Y is not continuous, even when a binary instrumental variable (IV) Z is available. We show that, for any form of Y (continuous, binary, mixed, horizontal ellipsis ), there exists a decomposition Y = mu(0)(X) + mu(1)(X)D + error with E(error|Z,X) = 0, where mu 1(X)equivalent to E(Y1-Y0|complier,X) and 'compliers' are those who get ...
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作者：Wei, Bo; Peng, Limin; Zhang, Mei-Jie; Fine, Jason P.
作者单位：Emory University; Medical College of Wisconsin; University of North Carolina; University of North Carolina Chapel Hill
摘要：The causal effect of a treatment is of fundamental interest in the social, biological and health sciences. Instrumental variable (IV) methods are commonly used to determine causal treatment effects in the presence of unmeasured confounding. In this work, we study a new binary IV framework with randomly censored outcomes where we propose to quantify the causal treatment effect by the concept of complier quantile causal effect (CQCE). The CQCE is identifiable under weaker conditions than the com...
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作者：Mourtada, Jaouad; Gaiffas, Stephane; Scornet, Erwan
作者单位：Institut Polytechnique de Paris; Ecole Polytechnique; Centre National de la Recherche Scientifique (CNRS); Centre National de la Recherche Scientifique (CNRS); Universite Paris Cite; Universite PSL; Ecole Normale Superieure (ENS); Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI)
摘要：Random forest (RF) is one of the algorithms of choice in many supervised learning applications, be it classification or regression. The appeal of such tree-ensemble methods comes from a combination of several characteristics: a remarkable accuracy in a variety of tasks, a small number of parameters to tune, robustness with respect to features scaling, a reasonable computational cost for training and prediction, and their suitability in high-dimensional settings. The most commonly used RF varia...
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作者：Liu, Yi; Rockova, Veronika; Wang, Yuexi
作者单位：University of Chicago; University of Chicago
摘要：Few problems in statistics are as perplexing as variable selection in the presence of very many redundant covariates. The variable selection problem is most familiar in parametric environments such as the linear model or additive variants thereof. In this work, we abandon the linear model framework, which can be quite detrimental when the covariates impact the outcome in a non-linear way, and turn to tree-based methods for variable selection. Such variable screening is traditionally done by pr...
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作者：Heng, Siyu; Kang, Hyunseung; Small, Dylan S.; Fogarty, Colin B.
作者单位：University of Pennsylvania; University of Wisconsin System; University of Wisconsin Madison; Massachusetts Institute of Technology (MIT)
摘要：In many observational studies, the interest is in the effect of treatment on bad, aberrant outcomes rather than the average outcome. For such settings, the traditional approach is to define a dichotomous outcome indicating aberration from a continuous score and use the Mantel-Haenszel test with matched data. For example, studies of determinants of poor child growth use the World Health Organization's definition of child stunting being height-for-age z-score <= - 2. The traditional approach may...
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作者：Reimherr, Matthew; Meng, Xiao-Li; Nicolae, Dan L.
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Harvard University; University of Chicago
摘要：This paper outlines a framework for quantifying the prior's contribution to posterior inference in the presence of prior-likelihood discordance, a broader concept than the usual notion of prior-likelihood conflict. We achieve this dual purpose by extending the classic notion of prior sample size, M, in three directions: (I) estimating M beyond conjugate families; (II) formulating M as a relative notion that is as a function of the likelihood sample size k, M(k), which also leads naturally to a...
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作者：Stokell, Benjamin G.; Shah, Rajen D.; Tibshirani, Ryan J.
作者单位：University of Cambridge; Carnegie Mellon University
摘要：We propose a method for estimation in high-dimensional linear models with nominal categorical data. Our estimator, called SCOPE, fuses levels together by making their corresponding coefficients exactly equal. This is achieved using the minimax concave penalty on differences between the order statistics of the coefficients for a categorical variable, thereby clustering the coefficients. We provide an algorithm for exact and efficient computation of the global minimum of the resulting nonconvex ...
