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作者：Xue, Lingzhou; Zou, Hui
作者单位：University of Minnesota System; University of Minnesota Twin Cities
摘要：A sparse precision matrix can be directly translated into a sparse Gaussian graphical model under the assumption that the data follow a joint normal distribution. This neat property makes high-dimensional precision matrix estimation very appealing in many applications. However, in practice we often face nonnormal data, and variable transformation is often used to achieve normality. In this paper we consider the nonparanormal model that assumes that the variables follow a joint normal distribut...
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作者：Ren, Zhao; Zhou, Harrison H.
作者单位：Yale University
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作者：Koul, Hira L.; Mueller, Ursula U.; Schick, Anton
作者单位：Michigan State University; Texas A&M University System; Texas A&M University College Station; State University of New York (SUNY) System; Binghamton University, SUNY
摘要：This paper gives a general method for deriving limiting distributions of complete case statistics for missing data models from corresponding results for the model where all data are observed. This provides a convenient tool for obtaining the asymptotic behavior of complete case versions of established full data methods without lengthy proofs. The methodology is illustrated by analyzing three inference procedures for partially linear regression models with responses missing at random. We first ...
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作者：Anandkumar, Animashree; Tan, Vincent Y. F.; Huang, Furong; Willsky, Alan S.
作者单位：National University of Singapore; Agency for Science Technology & Research (A*STAR); A*STAR - Institute for Infocomm Research (I2R)
摘要：We consider the problem of high-dimensional Ising (graphical) model selection. We propose a simple algorithm for structure estimation based on the thresholding of the empirical conditional variation distances. We introduce a novel criterion for tractable graph families, where this method is efficient, based on the presence of sparse local separators between node pairs in the underlying graph. For such graphs, the proposed algorithm has a sample complexity of n = Omega(J(min)(-2) log p), where ...
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作者：Lam, Clifford; Yao, Qiwei
作者单位：University of London; London School Economics & Political Science; Peking University
摘要：This paper deals with the factor modeling for high-dimensional time series based on a dimension-reduction viewpoint. Under stationary settings, the inference is simple in the sense that both the number of factors and the factor loadings are estimated in terms of an eigenanalysis for a nonnegative definite matrix, and is therefore applicable when the dimension of time series is on the order of a few thousands. Asymptotic properties of the proposed method are investigated under two settings: (i)...
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作者：Gehrmann, Helene; Lauritzen, Steffen L.
作者单位：University of Oxford
摘要：We study the problem of estimability of means in undirected graphical Gaussian models with symmetry restrictions represented by a colored graph. Following on from previous studies, we partition the variables into sets of vertices whose corresponding means are restricted to being identical. We find a necessary and sufficient condition on the partition to ensure equality between the maximum likelihood and least-squares estimators of the mean.
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作者：Kato, Kengo
作者单位：Hiroshima University
摘要：This paper studies estimation in functional linear quantile regression in which the dependent variable is scalar while the covariate is a function, and the conditional quantile for each fixed quantile index is modeled as a linear functional of the covariate. Here we suppose that covariates are discretely observed and sampling points may differ across subjects, where the number of measurements per subject increases as the sample size. Also, we allow the quantile index to vary over a given subse...
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作者：Drton, Mathias; Goia, Aldo
作者单位：University of Chicago; University of Eastern Piedmont Amedeo Avogadro
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作者：Rousseau, Judith; Chopin, Nicolas; Liseo, Brunero
作者单位：Institut Polytechnique de Paris; ENSAE Paris; Sapienza University Rome
摘要：A stationary Gaussian process is said to be long-range dependent (resp., anti-persistent) if its spectral density f(lambda) can be written as f(lambda) = vertical bar lambda vertical bar(-2d) g(vertical bar lambda vertical bar), where 0 < 1/2 (resp., -1/2 < 0), and g is continuous and positive. We propose a novel Bayesian nonparametric approach for the estimation of the spectral density of such processes. We prove posterior consistency for both d and g, under appropriate conditions on the prio...
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作者：Ehm, Werner; Gneiting, Tilmann
作者单位：Ruprecht Karls University Heidelberg
摘要：Scoring rules assess the quality of probabilistic forecasts, by assigning a numerical score based on the predictive distribution and on the event or value that materializes. A scoring rule is proper if it encourages truthful reporting. It is local of order k if the score depends on the predictive density only through its value and the values of its derivatives of order up to k at the realizing event. Complementing fundamental recent work by Parry, Dawid and Lauritzen, we characterize the local...
