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作者：Tong, Xingwei; Gao, Fuqing; Chen, Kani; Cai, Dingjiao; Sun, Jianguo
作者单位：Beijing Normal University; Wuhan University; Hong Kong University of Science & Technology; Henan University of Economics & Law; University of Missouri System; University of Missouri Columbia
摘要：This paper discusses the transformed linear regression with non-normal error distributions, a problem that often occurs in many areas such as economics and social sciences as well as medical studies. The linear transformation model is an important tool in survival analysis partly due to its flexibility. In particular, it includes the Cox model and the proportional odds model as special cases when the error follows the extreme value distribution and the logistic distribution, respectively. Desp...
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作者：Bachoc, Francois; Leeb, Hannes; Potscher, Benedikt M.
作者单位：Universite de Toulouse; Universite Toulouse III - Paul Sabatier; University of Vienna
摘要：We consider inference post-model-selection in linear regression. In this setting, Berk et al. [Ann. Statist. 41 (2013a) 802-837] recently introduced a class of confidence sets, the so-called PoSI intervals, that cover a certain nonstandard quantity of interest with a user-specified minimal coverage probability, irrespective of the model selection procedure that is being used. In this paper, we generalize the PoSI intervals to confidence intervals for post-model-selection predictors.
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作者：Saegusa, Takumi
作者单位：University System of Maryland; University of Maryland College Park
摘要：We develop large sample theory for merged data from multiple sources. Main statistical issues treated in this paper are (1) the same unit potentially appears in multiple datasets from overlapping data sources, (2) duplicated items are not identified and (3) a sample from the same data source is dependent due to sampling without replacement. We propose and study a new weighted empirical process and extend empirical process theory to a dependent and biased sample with duplication. Specifically, ...
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作者：Wang, Nanwei; Rauh, Johannes; Massam, Helene
作者单位：York University - Canada; York University - Canada; Max Planck Society
摘要：The existence of the maximum likelihood estimate in a hierarchical log-linear model is crucial to the reliability of inference for this model. Determining whether the estimate exists is equivalent to finding whether the sufficient statistics vector t belongs to the boundary of the marginal polytope of the model. The dimension of the smallest face F-t containing t determines the dimension of the reduced model which should be considered for correct inference. For higher-dimensional problems, it ...
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作者：Hsu, Hsiang-Ling; Ing, Ching-Kang; Tong, Howell
作者单位：National University Kaohsiung; National Tsing Hua University; University of Electronic Science & Technology of China; University of London; London School Economics & Political Science
摘要：Consider finite parametric time series models. I have n observations and k models, which model should I choose on the basis of the data alone is a frequently asked question in many practical situations. This poses the key problem of selecting a model from a collection of candidate models, none of which is necessarily the true data generating process (DGP). Although existing literature on model selection is vast, there is a serious lacuna in that the above problem does not seem to have received...
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作者：Qin, Likuan; Todorov, Viktor
作者单位：Northwestern University; Northwestern University
摘要：This paper develops a nonparametric estimator for the Levy density of an asset price, following an Ito semimartingale, implied by short-maturity options. The asymptotic setup is one in which the time to maturity of the available options decreases, the mesh of the available strike grid shrinks and the strike range expands. The estimation is based on aggregating the observed option data into nonparametric estimates of the conditional characteristic function of the return distribution, the deriva...
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作者：Chen, Hao
作者单位：University of California System; University of California Davis
摘要：We propose a new framework for the detection of change-points in online, sequential data analysis. The approach utilizes nearest neighbor information and can be applied to sequences of multivariate observations or non-Euclidean data objects, such as network data. Different stopping rules are explored, and one specific rule is recommended due to its desirable properties. An accurate analytic approximation of the average run length is derived for the recommended rule, making it an easy off-the-s...
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作者：Hung, Kenneth; Fithian, William
作者单位：University of California System; University of California Berkeley; University of California System; University of California Berkeley
摘要：Many statistical experiments involve comparing multiple population groups. For example, a public opinion poll may ask which of several political candidates commands the most support; a social scientific survey may report the most common of several responses to a question; or, a clinical trial may compare binary patient outcomes under several treatment conditions to determine the most effective treatment. Having observed the winner (largest observed response) in a noisy experiment, it is natura...
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作者：Qin, Qian; Hobert, James P.
作者单位：State University System of Florida; University of Florida
摘要：The use of MCMC algorithms in high dimensional Bayesian problems has become routine. This has spurred so-called convergence complexity analysis, the goal of which is to ascertain how the convergence rate of a Monte Carlo Markov chain scales with sample size, n, and/or number of covariates, p. This article provides a thorough convergence complexity analysis of Albert and Chib's [J. Amer. Statist. Assoc. 88 (1993) 669-679] data augmentation algorithm for the Bayesian probit regression model. The...
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作者：Bevilacqua, Moreno; Faouzi, Tarik; Furrer, Reinhard; Porcu, Emilio
作者单位：Universidad de Valparaiso; Universidad del Bio-Bio; University of Zurich; University of Zurich; Newcastle University - UK; Universidad de Atacama
摘要：We study estimation and prediction of Gaussian random fields with covariance models belonging to the generalized Wendland (GW) class, under fixed domain asymptotics. As for the Matern case, this class allows for a continuous parameterization of smoothness of the underlying Gaussian random field, being additionally compactly supported. The paper is divided into three parts: first, we characterize the equivalence of two Gaussian measures with GW covariance function, and we provide sufficient con...
