2期

最新文章

• Likelihood approach for marginal proportional hazards regression in the presence of dependent censoring AI翻译
  作者：Zeng, DL
  作者单位：University of North Carolina; University of North Carolina Chapel Hill
  摘要：In many public health problems, an important goal is to identify the effect of some treatment/intervention on the risk of failure for the whole population. A marginal proportional hazards regression model is often used to analyze such an effect. When dependent censoring is explained by many auxiliary covariates, we utilize two working models to condense high-dimensional covariates to achieve dimension reduction. Then the estimator of the treatment effect is obtained by maximizing a pseudo-like...
• On the Chernoff bound for efficiency of quantum hypothesis testing AI翻译
  作者：Kargin, V
  作者单位：Cornerstone Research
  摘要：The paper estimates the Chernoff rate for the efficiency of quantum IF hypothesis testing. For both joint and separate measurements, approximate bounds for the rate are given if both states are mixed, and exact expressions are derived if at least one of the states is pure. The efficiencies of tests with separate and joint measurements are compared. The results are illustrated by a test of quantum entanglement.
• Multiprocess parallel antithetic coupling for backward and forward Markov chain Monte Carlo AI翻译
  作者：Craiu, RV; Meng, XL
  作者单位：University of Toronto; Harvard University
  摘要：Antithetic coupling is a general stratification strategy for reducing Monte Carlo variance without increasing the simulation size. The use of the antithetic principle in the Monte Carlo literature typically employs two strata via antithetic quantile coupling. We demonstrate here that further stratification, obtained by using k > 2 (e.g., k = 3-10) antithetically coupled variates, can offer substantial additional gain in Monte Carlo efficiency, in terms of both variance and bias. The reason for...
• Spike and slab variable selection: Frequentist and Bayesian strategies AI翻译
  作者：Ishwaran, H; Rao, JS
  作者单位：Cleveland Clinic Foundation; University System of Ohio; Case Western Reserve University
  摘要：Variable selection in the linear regression model takes many apparent faces from both frequentist and Bayesian standpoints. In this paper we introduce a variable selection method referred to as a rescaled spike and slab model. We study the importance of prior hierarchical specifications and draw connections to frequentist generalized ridge regression estimation. Specifically, we study the usefulness of continuous bimodal priors to model hypervariance parameters, and the effect scaling has on t...
• Functionals of Dirichlet processes, the Cifarelli-Regazzini identity and Beta-Gamma processes AI翻译
  作者：James, LF
  作者单位：Hong Kong University of Science & Technology
  摘要：Suppose that P theta(g) is a linear functional of a Dirichlet process with shape theta H, where theta > 0 is the total mass and H is a fixed probability measure. This paper describes how one can use the well-known Bayesian prior to posterior analysis of the Dirichlet process, and a posterior calculus for Gamma processes to ascertain properties of linear functionals of Dirichlet processes. In particular, in conjunction with a Gamma identity, we show easily that a generalized Cauchy-Stieltjes tr...
• Data-driven rate-optimal specification testing in regression models AI翻译
  作者：Guerre, E; Lavergne, P
  作者单位：Sorbonne Universite; Universite PSL; Ecole des Hautes Etudes en Sciences Sociales (EHESS); Universite de Toulouse; Universite Toulouse 1 Capitole; Centre National de la Recherche Scientifique (CNRS)
  摘要：We propose new data-driven smooth tests for a parametric regression function. The smoothing parameter is selected through a new criterion that favors a large smoothing parameter under the null hypothesis. The resulting test is adaptive rate-optimal and consistent against Pitman local alternatives approaching the parametric model at a rate arbitrarily close to I/root n. Asymptotic critical values come from the standard normal distribution and the bootstrap can be used in small samples. A genera...
• Default priors for Gaussian processes AI翻译
  作者：Paulo, R
  摘要：Motivated by the statistical evaluation of complex computer models, we deal with the issue of objective prior specification for the parameters of Gaussian processes. In particular, we derive the Jeffreys-rule, independence Jeffreys and reference priors for this situation, and prove that the resulting posterior distributions are proper under a quite general set of conditions. A proper flat prior strategy, based on maximum likelihood estimates, is also considered, and all priors are then compare...
• Extremal quantile regression AI翻译
  作者：Chernozhukov, V
  作者单位：Massachusetts Institute of Technology (MIT)
  摘要：Quantile regression is an important tool for estimation of conditional quantiles of a response Y given a vector of covariates X. It can be used to measure the effect of covariates not only in the center of a distribution. but also in the upper and lower tails. This paper develops a theory of quantile regression in the tails. Specifically, it obtains the large sample properties of extremal (extreme order and intermediate order) quantile regression estimators for the linear quantile regression m...