Journal of the Royal Statistical Society: Series B

最新文章

• Extensible grids: uniform sampling on a space filling curve AI翻译
  作者：He, Zhijian; Owen, Art B.
  作者单位：Tsinghua University; Stanford University
  摘要：We study the properties of points in [0,1]d generated by applying Hilbert's space filling curve to uniformly distributed points in [0,1]. For deterministic sampling we obtain a discrepancy of O(n-1/d) for d2. For random stratified sampling, and scrambled van der Corput points, we derive a mean-squared error of O(n-1-2/d) for integration of Lipschitz continuous integrands, when d3. These rates are the same as those obtained by sampling on d-dimensional grids and they show a deterioration with i...
• Drift estimation in sparse sequential dynamic imaging, with application to nanoscale fluorescence microscopy AI翻译
  作者：Hartmann, Alexander; Huckemann, Stephan; Dannemann, Joern; Laitenberger, Oskar; Geisler, Claudia; Egner, Alexander; Munk, Axel
  作者单位：University of Gottingen; Max Planck Society
  摘要：A major challenge in many modern superresolution fluorescence microscopy techniques at the nanoscale lies in the correct alignment of long sequences of sparse but spatially and temporally highly resolved images. This is caused by the temporal drift of the protein structure, e.g. due to temporal thermal inhomogeneity of the object of interest or its supporting area during the observation process. We develop a simple semiparametric model for drift correction in single-marker switching microscopy...
• On the coverage bound problem of empirical likelihood methods for time series AI翻译
  作者：Zhang, Xianyang; Shao, Xiaofeng
  作者单位：University of Missouri System; University of Missouri Columbia; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：The upper bounds on the coverage probabilities of the confidence regions based on blockwise empirical likelihood and non-standard expansive empirical likelihood methods for time series data are investigated via studying the probability of violating the convex hull constraint. The large sample bounds are derived on the basis of the pivotal limit of the blockwise empirical log-likelihood ratio obtained under fixed b asymptotics, which has recently been shown to provide a more accurate approximat...
• 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...