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作者：Wheeler, M. W.; Dunson, D. B.; Herring, A. H.
作者单位：Centers for Disease Control & Prevention - USA; National Institute for Occupational Safety & Health (NIOSH); Duke University
摘要：We consider shape- restricted nonparametric regression on a closed set X. R, where it is reasonable to assume that the function has no more than H local extrema interior to X. Following a Bayesian approach we develop a nonparametric prior over a novel class of local extremum splines. This approach is shown to be consistent when modelling any continuously differentiable function within the class considered, and we use it to develop methods for testing hypotheses on the shape of the curve. Sampl...
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作者：Ollier, E.; Viallon, V.
作者单位：Ecole Normale Superieure de Lyon (ENS de LYON); Universite Gustave-Eiffel; Universite Claude Bernard Lyon 1
摘要：We consider the estimation of regression models on strata defined using a categorical covariate, in order to identify interactions between this categorical covariate and the other predictors. A basic approach requires the choice of a reference stratum. We show that the performance of a penalized version of this approach depends on this arbitrary choice, and propose an approach that bypasses this at almost no additional computational cost. Regarding model selection consistency, our proposal mim...
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作者：She, Yiyuan
作者单位：State University System of Florida; Florida State University
摘要：This paper studies simultaneous feature selection and extraction in supervised and unsupervised learning. We propose and investigate selective reduced rank regression for constructing optimal explanatory factors from a parsimonious subset of input features. The proposed estimators enjoy sharp oracle inequalities, and with a predictive information criterion for model selection, they adapt to unknown sparsity by controlling both rank and row support of the coefficient matrix. A class of algorith...
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作者：Yu, Tao; Li, Pengfei; Qin, Jing
作者单位：National University of Singapore; University of Waterloo; National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID)
摘要：In this paper, we propose a method for estimating the probability density functions in a two-sample problem where the ratio of the densities is monotone. This problem has been widely identified in the literature, but effective solution methods, in which the estimates should be probability densities and the corresponding density ratio should inherit monotonicity, are unavailable. If these conditions are not satisfied, the applications of the resultant density estimates might be limited. We prop...
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作者：Cuevas, F.; Porcu, E.; Bevilacqua, M.
作者单位：Aalborg University; Newcastle University - UK; Universidad de Valparaiso
摘要：We offer a dual view of the dimple problem related to space-time correlation functions in terms of their contours. We find that the dimple property (Kent et al., 2011) in the Gneiting class of correlations is in one-to-one correspondence with nonmonotonicity of the parametric curve describing the associated contour lines. Further, we show that given such a nonmonotonic parametric curve associated with a given level set, all the other parametric curves at smaller levels inherit the nonmonotonic...
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作者：Tsay, Ruey S.; Pourahmadi, Mohsen
作者单位：University of Chicago; Texas A&M University System; Texas A&M University College Station
摘要：Ensuring positive definiteness of an estimated structured correlation matrix is challenging. We show that reparameterizing Cholesky factors of correlation matrices using hyperspherical coordinates or angles provides a flexible and effective solution. Once a structured correlation matrix is identified, the corresponding angles and hence the constrained correlations may be estimated by maximum likelihood. Consistency and asymptotic normality of the maximum likelihood estimators of the angles are...
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作者：Baba, Takamichi; Kanemori, Takayuki; Ninomiya, Yoshiyuki
作者单位：Shionogi & Company Limited; Kyushu University
摘要：For marginal structural models, which play an important role in causal inference, we consider a model selection problem within a semiparametric framework using inverse-probability-weighted estimation or doubly robust estimation. In this framework, the modelling target is a potential outcome that may be missing, so there is no classical information criterion. We define a mean squared error for treating the potential outcome and derive an asymptotic unbiased estimator as a criterion using an ign...
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作者：Zhou, Qing; Min, Seunghyun
作者单位：University of California System; University of California Los Angeles
摘要：Quantifying the uncertainty in penalized regression under group sparsity is an important open question. We establish, under a high-dimensional scaling, the asymptotic validity of a modified parametric bootstrap method for the group lasso, assuming a Gaussian error model and mild conditions on the design matrix and the true coefficients. Simulation of bootstrap samples provides simultaneous inferences on large groups of coefficients. Through extensive numerical comparisons, we demonstrate that ...
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作者：Ding, P.; Vanderweele, T. J.; Robins, J. M.
作者单位：University of California System; University of California Berkeley; Harvard University; Harvard T.H. Chan School of Public Health
摘要：Drawing causal inference with observational studies is the central pillar of many disciplines. One sufficient condition for identifying the causal effect is that the treatment-outcome relationship is unconfounded conditional on the observed covariates. It is often believed that the more covariates we condition on, the more plausible this unconfoundedness assumption is. This belief has had a huge impact on practical causal inference, suggesting that we should adjust for all pretreatment covaria...
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作者：Constantinou, P.; Kokoszka, P.; Reimherr, M.
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Colorado State University System; Colorado State University Fort Collins; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：Separability is a common simplifying assumption on the covariance structure of spatiotemporal functional data. We present three tests of separability, one a functional extension of the Monte Carlo likelihood method of Mitchell et al. (2006) and two based on quadratic forms. Our tests are based on asymptotic distributions of maximum likelihood estimators and do not require Monte Carlo simulation. The main theoretical contribution of this paper is the specification of the joint asymptotic distri...
