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作者：Chang, Lo-Bin; Geman, Donald
作者单位：University System of Ohio; Ohio State University; Johns Hopkins University
摘要：In recent years, reproducibility has emerged as a key factor in evaluating x applications of statistics to the biomedical sciences, for example, learning predictors of disease phenotypes from high-throughput omics data. In particular, validation is undermined when error rates on newly acquired data are sharply higher than those originally reported. More precisely, when data are collected from m studies representing possibly different subphenotypes, more generally different mixtures of subpheno...
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作者：Sun, Qiang; Zhu, Hongtu; Liu, Yufeng; Ibrahim, Joseph G.
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill
摘要：The aim of this article is to develop a sparse projection regression modeling (SPReM) framework to perform multivariate regression modeling with a large number of responses and a multivariate covariate of interest. We propose two novel heritability ratios to simultaneously perform dimension reduction, response selection, estimation, and testing, while explicitly accounting for correlations among multivariate responses. Our SPReM is devised to specifically address the low statistical power issu...
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作者：Galvao, Antonio F.; Wang, Liang
作者单位：University of Iowa; University of Wisconsin System; University of Wisconsin Milwaukee
摘要：This article studies identification, estimation, and inference of general unconditional treatment effects models with continuous treatment under the ignorability assumption. We show identification of the parameters of interest, the dose-response functions, under the assumption that selection to treatment is based on observables. We propose a semiparametric two-step estimator, and consider estimation of the dose-response functions through moment restriction models with generalized residual func...
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作者：Pedeli, Xanthi; Davison, Anthony C.; Fokianos, Konstantinos
作者单位：Athens University of Economics & Business; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; University of Cyprus
摘要：Saddlepoint techniques have been used successfully in many applications, owing to the high accuracy with which they can approximate intractable densities and tail probabilities. This article concerns their use for the estimation of high-order integer-valued autoregressive, INAR(p), processes. Conditional least squares estimation and maximum likelihood estimation have been proposed for INAR(p) models, but the first is inefficient for estimating parametric models, and the second becomes difficul...
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作者：Radchenko, Peter; Qiao, Xinghao; James, Gareth M.
作者单位：University of Southern California
摘要：The regression problem involving functional predictors has many important applications and a number of functional regression methods have been developed. However, a common complication in functional data analysis is one of sparsely observed curves, that is predictors that are observed, with error, on a small subset of the possible time points. Such sparsely observed data induce an errors-in-variables model, where one must account for measurement error in the functional predictors. Faced with s...
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作者：Scealy, J. L.; de Caritat, Patrice; Grunsky, Eric C.; Tsagris, Michail T.; Welsh, A. H.
作者单位：Australian National University; Geoscience Australia; Australian National University; Natural Resources Canada; Lands & Minerals Sector - Natural Resources Canada; Geological Survey of Canada; Australian National University
摘要：Geochemical surveys collect sediment or rock samples, measure the concentration of chemical elements, and report these typically either in weight percent or in parts per million (ppm). There are usually a large number of elements measured and the distributions are often skewed, containing many potential outliers. We present a new robust principal component analysis (PCA) method for geochemical survey data, that involves first transforming the compositional data onto a manifold using a relative...
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作者：Chatterjee, A.; Lahiri, S. N.
作者单位：Indian Statistical Institute; Indian Statistical Institute Delhi; North Carolina State University
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作者：Simon, Noah; Tibshirani, Robert
作者单位：University of Washington; University of Washington Seattle; Stanford University; Stanford University
摘要：To date testing interactions in high dimensions is a challenging task. Existing methods often have issues with sensitivity to modeling assumptions and heavily asymptotic nominal p-values. To help alleviate these issues, we propose a permutation-based method for testing marginal interactions with a binary response. Our method searches for pairwise correlations that differ between classes. In this article, we compare our method on real and simulated data to the standard approach of running many ...
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作者：Zhang, Yichi; Laber, Eric B.
作者单位：North Carolina State University
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作者：Cook, R. Dennis; Zhang, Xin
作者单位：University of Minnesota System; University of Minnesota Twin Cities; State University System of Florida; Florida State University
摘要：Envelopes were recently proposed by Cook, Li and Chiaromonte as a method for reducing estimative and predictive variations in multivariate linear regression. We extend their formulation, proposing a general definition of an envelope and a general framework for adapting envelope methods to any estimation procedure. We apply the new envelope methods to weighted least squares, generalized linear models and Cox regression. Simulations and illustrative data analysis show the potential for envelope ...
