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作者：Park, C.; Kang, H.
作者单位：University of Wisconsin System; University of Wisconsin Madison
摘要：Although many estimators for network treatment effects have been proposed, their optimality properties, in terms of semiparametric efficiency, have yet to be resolved. We present a simple yet flexible asymptotic framework for deriving the efficient influence function and the semiparametric efficiency lower bound for a family of network causal effects under partial interference. An important corollary of our results is that one existing estimator, that proposed by , is locally efficient. We als...
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作者：Ciocanea-Teodorescu, I; Gabriel, E. E.; Sjolander, A.
作者单位：Karolinska Institutet; University of Copenhagen
摘要：One of the main threats to the validity of causal effect estimates from observational data is the existence of unmeasured confounders. A plethora of methods has been proposed to quantify deviation from conditional exchangeability, which arises when confounding is not properly accounted for, with each method having its own set of limitations and underlying assumptions. Few methods both scale well with the increasing complexity of potential measured confounders and avoid making strong simplifyin...
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作者：Xu, Jason; Lange, Kenneth
作者单位：Duke University; University of California System; University of California Los Angeles
摘要：This paper addresses the task of estimating a covariance matrix under a patternless sparsity assumption. In contrast to existing approaches based on thresholding or shrinkage penalties, we propose a likelihood-based method that regularizes the distance from the covariance estimate to a symmetric sparsity set. This formulation avoids unwanted shrinkage induced by more common norm penalties, and enables optimization of the resulting nonconvex objective by solving a sequence of smooth, unconstrai...
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作者：Ying, Chao; Yu, Zhou
作者单位：East China Normal University
摘要：We consider Frechet sufficient dimension reduction with responses being complex random objects in a metric space and high-dimensional Euclidean predictors. We propose a novel approach, called the weighted inverse regression ensemble method, for linear Frechet sufficient dimension reduction. The method is further generalized as a new operator defined on reproducing kernel Hilbert spaces for nonlinear Frechet sufficient dimension reduction. We provide theoretical guarantees for the new method vi...
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作者：Sei, T.; Komaki, F.
作者单位：University of Tokyo
摘要：A Bayesian prediction problem for the two-dimensional Wishart model is investigated within the framework of decision theory. The loss function is the Kullback-Leibler divergence. We construct a scale-invariant and permutation-invariant prior distribution that shrinks the correlation coefficient. The prior is the geometric mean of the right invariant prior with respect to permutation of the indices, and is characterized by a uniform distribution for Fisher's z-transformation of the correlation ...
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作者：Zhao, Peng; Yang, Yun; He, Qiao-Chu
作者单位：Texas A&M University System; Texas A&M University College Station; University of Illinois System; University of Illinois Urbana-Champaign; Southern University of Science & Technology
摘要：Many statistical estimators for high-dimensional linear regression are M-estimators, formed through minimizing a data-dependent square loss function plus a regularizer. This work considers a new class of estimators implicitly defined through a discretized gradient dynamic system under overparameterization. We show that, under suitable restricted isometry conditions, overparameterization leads to implicit regularization: if we directly apply gradient descent to the residual sum of squares with ...
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作者：Heinrich-Mertsching, Claudio; Fissler, Tobias
作者单位：Vienna University of Economics & Business
摘要：A statistical functional is said to be elicitable if there exists a loss or scoring function under which the functional is the optimal point forecast in expectation. While the mean and quantiles are elicitable, it has been shown in that the mode is not elicitable if the true distribution can follow any Lebesgue density. We strengthen the result of substantially, showing that the mode is not elicitable if the true distribution can be any strongly unimodal distribution with continuous Lebesgue d...
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作者：McKeague, Ian W.; Zhang, Xin
作者单位：Columbia University; State University System of Florida; Florida State University
摘要：We consider the problem of testing for the presence of linear relationships between large sets of random variables based on a postselection inference approach to canonical correlation analysis. The challenge is to adjust for the selection of subsets of variables having linear combinations with maximal sample correlation. To this end, we construct a stabilized one-step estimator of the Euclidean norm of the canonical correlations maximized over subsets of variables of prespecified cardinality. ...
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作者：Wang, Rui; Xu, Wangli
作者单位：Renmin University of China; Renmin University of China
摘要：This paper is concerned with the problem of comparing the population means of two groups of independent observations. An approximate randomization test procedure based on the test statistic of is proposed. The asymptotic behaviour of the test statistic, as well as the randomized statistic, is studied under weak conditions. In our theoretical framework, observations are not assumed to be identically distributed even within groups. No condition on the eigenstructure of the covariance matrices is...
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作者：Henzi, Alexander; Ziegel, Johanna F.
作者单位：University of Bern
