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作者：Mukhopadhyay, Minerva; Dunson, David B.
作者单位：Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Kanpur; Duke University
摘要：We consider the problem of computationally efficient prediction with high dimensional and highly correlated predictors when accurate variable selection is effectively impossible. Direct application of penalization or Bayesian methods implemented with Markov chain Monte Carlo can be computationally daunting and unstable. A common solution is first stage dimension reduction through screening or projecting the design matrix to a lower dimensional hyper-plane. Screening is highly sensitive to thre...
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作者：Ma, Xinwei; Wang, Jingshen
作者单位：University of California System; University of California San Diego; University of California System; University of California Berkeley
摘要：Inverse probability weighting (IPW) is widely used in empirical work in economics and other disciplines. As Gaussian approximations perform poorly in the presence of small denominators, trimming is routinely employed as a regularization strategy. However, ad hoc trimming of the observations renders usual inference procedures invalid for the target estimand, even in large samples. In this article, we first show that the IPW estimator can have different (Gaussian or non-Gaussian) asymptotic dist...
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作者：Feng, Xiangnan; Li, Tengfei; Song, Xinyuan; Zhu, Hongtu
作者单位：Southwest Jiaotong University; University of North Carolina; University of North Carolina Chapel Hill; Chinese University of Hong Kong; University of North Carolina; University of North Carolina Chapel Hill
摘要：Medical imaging has become an increasingly important tool in screening, diagnosis, prognosis, and treatment of various diseases given its information visualization and quantitative assessment. The aim of this article is to develop a Bayesian scalar-on-image regression model to integrate high-dimensional imaging data and clinical data to predict cognitive, behavioral, or emotional outcomes, while allowing for nonignorable missing outcomes. Such a nonignorable nonresponse consideration is motiva...
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作者：Bradley, Jonathan R.; Holan, Scott H.; Wikle, Christopher K.
作者单位：State University System of Florida; Florida State University; University of Missouri System; University of Missouri Columbia
摘要：We introduce a Bayesian approach for analyzing (possibly) high-dimensional dependent data that are distributed according to a member from the natural exponential family of distributions. This problem requires extensive methodological advancements, as jointly modeling high-dimensional dependent data leads to the so-called big n problem. The computational complexity of the big n problem is further exacerbated when allowing for non-Gaussian data models, as is the case here. Thus, we develop new c...
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作者：Lei, Jing
作者单位：Carnegie Mellon University
摘要：Cross-validation is one of the most popular model and tuning parameter selection methods in statistics and machine learning. Despite its wide applicability, traditional cross-validation methods tend to overfit, due to the ignorance of the uncertainty in the testing sample. We develop a novel statistically principled inference tool based on cross-validation that takes into account the uncertainty in the testing sample. This method outputs a set of highly competitive candidate models containing ...
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作者：Cook, Richard J.
作者单位：University of Waterloo
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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：Yang, Bingduo; Long, Wei; Peng, Liang; Cai, Zongwu
作者单位：Sun Yat Sen University; Tulane University; University System of Georgia; Georgia State University; University of Kansas
摘要：We use ten common macroeconomic variables to test for the predictability of the quarterly growth rate of house price index (HPI) in the United States during 1975:Q1-2018:Q2. We extend the instrumental variable based Wald statistic (IVX-KMS) proposed by Kostakis, Magdalinos, and Stamatogiannis to a new instrumental variable based Wald statistic (IVX-AR) which accounts for serial correlation and heteroscedasticity in the error terms of the linear predictive regression model. Simulation results s...
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作者：Li, Xiudi; Shojaie, Ali
作者单位：University of Washington; University of Washington Seattle
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作者：Johnson, S. R.; Henderson, D. A.; Boys, R. J.
作者单位：Newcastle University - UK
摘要：Ranked data arise in many areas of application ranging from the ranking of up-regulated genes for cancer to the ranking of academic statistics journals. Complications can arise when rankers do not report a full ranking of all entities; for example, they might only report their top-M ranked entities after seeing some or all entities. It can also be useful to know whether rankers are equally informative, and whether some entities are effectively judged to be exchangeable. Revealing subgroup stru...
