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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...
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作者：Ji, Pengsheng; Jin, Jiashun
作者单位：Cornell University; Carnegie Mellon University
摘要：Consider a linear model Y = X beta + z, z similar to N(0, I-n). Here, X = X-n,X-p, where both p and n are large, but p > n. We model the rows of X as lid. samples from N(0, 1/n Omega), where Omega is a p x p correlation matrix, which is unknown to us but is presumably sparse. The vector beta is also unknown but has relatively few nonzero coordinates, and we are interested in identifying these nonzeros. We propose the Univariate Penalization Screeing (UPS) for variable selection. This is a scre...
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作者：Delaigle, Aurore; Hall, Peter
作者单位：University of Melbourne; University of California System; University of California Davis
摘要：The partial least squares procedure was originally developed to estimate the slope parameter in multivariate parametric models. More recently it has gained popularity in the functional data literature. There, the partial least squares estimator of slope is either used to construct linear predictive models, or as a tool to project the data onto a one-dimensional quantity that is employed for further statistical analysis. Although the partial least squares approach is often viewed as an attracti...
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作者：Guntuboyina, Adityanand
作者单位：University of Pennsylvania
摘要：We present a minimax optimal solution to the problem of estimating a compact, convex set from finitely many noisy measurements of its support function. The solution is based on appropriate regularizations of the least squares estimator. Both fixed and random designs are considered.
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作者：Arias-Castro, Ery; Bubeck, Sebastien; Lugosi, Gabor
作者单位：University of California System; University of California San Diego; Princeton University; Pompeu Fabra University; ICREA
摘要：We consider the hypothesis testing problem of deciding whether an observed high-dimensional vector has independent normal components or, alternatively, if it has a small subset of correlated components. The correlated components may have a certain combinatorial structure known to the statistician. We establish upper and lower bounds for the worst-case (minimax) risk in terms of the size of the correlated subset, the level of correlation, and the structure of the class of possibly correlated se...
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作者：Colombo, Diego; Maathuis, Marloes H.; Kalisch, Markus; Richardson, Thomas S.
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; University of Washington; University of Washington Seattle
摘要：We consider the problem of learning causal information between random variables in directed acyclic graphs (DAGs) when allowing arbitrarily many latent and selection variables. The FCI (Fast Causal Inference) algorithm has been explicitly designed to infer conditional independence and causal information in such settings. However, FCI is computationally infeasible for large graphs. We therefore propose the new RFCI algorithm, which is much faster than FCI. In some situations the output of RFCI ...
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作者：Dette, Holger; Melas, Viatcheslav B.; Shpilev, Petr
作者单位：Ruhr University Bochum; Saint Petersburg State University
摘要：This paper is devoted to the explicit construction of optimal designs for discrimination between two polynomial regression models of degree n - 2 and n. In a fundamental paper, Atkinson and Fedorov [Biometrika 62 (1975a) 57-70] proposed the T-optimality criterion for this purpose. Recently, Atkinson [MODA 9, Advances in Model-Oriented Design and Analysis (2010) 9-16] determined T-optimal designs for polynomials up to degree 6 numerically and based on these results he conjectured that the suppo...
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作者：Liu, Jingchen; Xu, Gongjun
作者单位：Columbia University
摘要：In this paper, we derive tail approximations of integrals of exponential functions or Gaussian random fields with varying mean functions and approximations of the associated point processes. This study is motivated naturally by multiple applications such as hypothesis testing for spatial models and financial applications.
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作者：Tang, Runlong; Banerjee, Moulinath; Kosorok, Michael R.
作者单位：Princeton University; University of Michigan System; University of Michigan; University of North Carolina; University of North Carolina Chapel Hill
摘要：In this paper, we study the nonparametric maximum likelihood estimator for an event time distribution function at a point in the current status model with observation times supported on a grid of potentially unknown sparsity and with multiple subjects sharing the same observation time. This is of interest since observation time ties occur frequently with current status data. The grid resolution is specified as cn(-gamma) with c > 0 being a scaling constant and gamma > 0 regulating the sparsity...
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作者：Bai, Jushan; Li, Kunpeng
作者单位：Columbia University; Tsinghua University; University of International Business & Economics; Central University of Finance & Economics
摘要：This paper considers the maximum likelihood estimation of factor models of high dimension, where the number of variables (N) is comparable with or even greater than the number of observations (T). An inferential theory is developed. We establish not only consistency but also the rate of convergence and the limiting distributions. Five different sets of identification conditions are considered. We show that the distributions of the MLE estimators depend on the identification restrictions. Unlik...
