2016

最新文章

• Non-parametric estimation of finite mixtures from repeated measurements AI翻译
  作者：Bonhomme, Stephane; Jochmans, Koen; Robin, Jean-Marc
  作者单位：University of Chicago; Institut d'Etudes Politiques Paris (Sciences Po); University of London; University College London
  摘要：This paper provides methods to estimate finite mixtures from data with repeated measurements non-parametrically. We present a constructive identification argument and use it to develop simple two-step estimators of the component distributions and all their functionals. We discuss a computationally efficient method for estimation and derive asymptotic theory. Simulation experiments suggest that our theory provides confidence intervals with good coverage in small samples.
• The lasso for high dimensional regression with a possible change point AI翻译
  作者：Lee, Sokbae; Seo, Myung Hwan; Shin, Youngki
  作者单位：Seoul National University (SNU); University of London; London School Economics & Political Science; University of London; London School Economics & Political Science; Western University (University of Western Ontario)
  摘要：We consider a high dimensional regression model with a possible change point due to a covariate threshold and develop the lasso estimator of regression coefficients as well as the threshold parameter. Our lasso estimator not only selects covariates but also selects a model between linear and threshold regression models. Under a sparsity assumption, we derive non-asymptotic oracle inequalities for both the prediction risk and the l(1)-estimation loss for regression coefficients. Since the lasso...
• Principal causal effect identification and surrogate end point evaluation by multiple trials AI翻译
  作者：Jiang, Zhichao; Ding, Peng; Geng, Zhi
  作者单位：Peking University; University of California System; University of California Berkeley
  摘要：Principal stratification is a causal framework to analyse randomized experiments with a post-treatment variable between the treatment and end point variables. Because the principal strata defined by the potential outcomes of the post-treatment variable are not observable, we generally cannot identify the causal effects within principal strata. Motivated by a real data set of phase III adjuvant colon cancer clinical trials, we propose approaches to identifying and estimating the principal causa...
• Sequential selection procedures and false discovery rate control AI翻译
  作者：G'Sell, Max Grazier; Wager, Stefan; Chouldechova, Alexandra; Tibshirani, Robert
  作者单位：Carnegie Mellon University; Stanford University
  摘要：We consider a multiple-hypothesis testing setting where the hypotheses are ordered and one is only permitted to reject an initial contiguous block H1,...,Hk of hypotheses. A rejection rule in this setting amounts to a procedure for choosing the stopping point k. This setting is inspired by the sequential nature of many model selection problems, where choosing a stopping point or a model is equivalent to rejecting all hypotheses up to that point and none thereafter. We propose two new testing p...
• An M-estimator of spatial tail dependence AI翻译
  作者：Einmahl, John H. J.; Kiriliouk, Anna; Krajina, Andrea; Segers, Johan
  作者单位：Tilburg University; Universite Catholique Louvain; University of Gottingen
  摘要：Tail dependence models for distributions attracted to a max-stable law are fitted by using observations above a high threshold. To cope with spatial, high dimensional data, a rank-based M-estimator is proposed relying on bivariate margins only. A data-driven weight matrix is used to minimize the asymptotic variance. Empirical process arguments show that the estimator is consistent and asymptotically normal. Its finite sample performance is assessed in simulation experiments involving popular m...
• Simulation of multivariate diffusion bridges AI翻译
  作者：Bladt, Mogens; Finch, Samuel; Sorensen, Michael
  作者单位：Universidad Nacional Autonoma de Mexico; University of Copenhagen
  摘要：We propose simple methods for multivariate diffusion bridge simulation, which plays a fundamental role in simulation-based likelihood and Bayesian inference for stochastic differential equations. By a novel application of classical coupling methods, the new approach generalizes a previously proposed simulation method for one-dimensional bridges to the multivariate setting. First a method of simulating approximate, but often very accurate, diffusion bridges is proposed. These approximate bridge...
• Bayesian regularization of the length of memory in reversible sequences AI翻译
  作者：Bacallado, Sergio; Pande, Vijay; Favaro, Stefano; Trippa, Lorenzo
  作者单位：Stanford University; University of Turin; Collegio Carlo Alberto; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute
  摘要：Variable order Markov chains have been used to model discrete sequential data in a variety of fields. A host of methods exist to estimate the history-dependent lengths of memory which characterize these models and to predict new sequences. In several applications, the data-generating mechanism is known to be reversible, but combining this information with the procedures mentioned is far from trivial. We introduce a Bayesian analysis for reversible dynamics, which takes into account uncertainty...
• Statistics of heteroscedastic extremes AI翻译
  作者：Einmahl, John H. J.; de Haan, Laurens; Zhou, Chen
  作者单位：Tilburg University; Erasmus University Rotterdam - Excl Erasmus MC; Erasmus University Rotterdam; Universidade de Lisboa; European Central Bank; De Nederlandsche Bank NV
  摘要：We extend classical extreme value theory to non-identically distributed observations. When the tails of the distribution are proportional much of extreme value statistics remains valid. The proportionality function for the tails can be estimated non-parametrically along with the (common) extreme value index. For a positive extreme value index, joint asymptotic normality of both estimators is shown; they are asymptotically independent. We also establish asymptotic normality of a forecasted high...
• Using post-outcome measurement information in censoring-by-death problems AI翻译
  作者：Yang, Fan; Small, Dylan S.
  作者单位：University of Chicago; University of Pennsylvania
  摘要：Many clinical studies on non-mortality outcomes such as quality of life suffer from the problem that the non-mortality outcome can be censored by death, i.e. the non-mortality outcome cannot be measured if the subject dies before the time of measurement. To address the problem that this censoring by death is informative, it is of interest to consider the average effect of the treatment on the non-mortality outcome among subjects whose measurement would not be censored under either treatment or...
• Robust inference in sample selection models AI翻译
  作者：Zhelonkin, Mikhail; Genton, Marc G.; Ronchetti, Elvezio
  作者单位：University of Lausanne; King Abdullah University of Science & Technology; University of Geneva
  摘要：The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function...