2017

最新文章

• Testing and confidence intervals for high dimensional proportional hazards models AI翻译
  作者：Fang, Ethan X.; Ning, Yang; Liu, Han
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Cornell University; Princeton University
  摘要：The paper considers the problem of hypothesis testing and confidence intervals in high dimensional proportional hazards models. Motivated by a geometric projection principle, we propose a unified likelihood ratio inferential framework, including score, Wald and partial likelihood ratio statistics for hypothesis testing. Without assuming model selection consistency, we derive the asymptotic distributions of these test statistics, establish their semiparametric optimality and conduct power analy...
• Convex clustering via l1 fusion penalization AI翻译
  作者：Radchenko, Peter; Mukherjee, Gourab
  作者单位：University of Southern California; University of Sydney
  摘要：We study the large sample behaviour of a convex clustering framework, which minimizes the sample within cluster sum of squares under an l(1) fusion constraint on the cluster centroids. This recently proposed approach has been gaining in popularity; however, its asymptotic properties have remained mostly unknown. Our analysis is based on a novel representation of the sample clustering procedure as a sequence of cluster splits determined by a sequence of maximization problems. We use this repres...
• Detection of adaptive shifts on phylogenies by using shifted stochastic processes on a tree AI翻译
  作者：Bastide, Paul; Mariadassou, Mahendra; Robin, Stephane
  作者单位：AgroParisTech; Universite Paris Saclay; INRAE; INRAE; Universite Paris Saclay
  摘要：Comparative and evolutive ecologists are interested in the distribution of quantitative traits between related species. The classical framework for these distributions consists of a random process running along the branches of a phylogenetic tree relating the species. We consider shifts in the process parameters, which reveal fast adaptation to changes of ecological niches. We show that models with shifts are not identifiable in general. Constraining the models to be parsimonious in the number...
• Provable sparse tensor decomposition AI翻译
  作者：Sun, Will Wei; Lu, Junwei; Liu, Han; Cheng, Guang
  作者单位：Yahoo! Inc; Princeton University; Purdue University System; Purdue University
  摘要：We propose a novel sparse tensor decomposition method, namely the tensor truncated power method, that incorporates variable selection in the estimation of decomposition components. The sparsity is achieved via an efficient truncation step embedded in the tensor power iteration. Our method applies to a broad family of high dimensional latent variable models, including high dimensional Gaussian mixtures and mixtures of sparse regressions. A thorough theoretical investigation is further conducted...
• The normal law under linear restrictions: simulation and estimation via minimax tilting AI翻译
  作者：Botev, Z. I.
  作者单位：University of New South Wales Sydney
  摘要：Simulation from the truncated multivariate normal distribution in high dimensions is a recurrent problem in statistical computing and is typically only feasible by using approximate Markov chain Monte Carlo sampling. We propose a minimax tilting method for exact independently and identically distributed data simulation from the truncated multivariate normal distribution. The new methodology provides both a method for simulation and an efficient estimator to hitherto intractable Gaussian integr...
• Fast moment-based estimation for hierarchical models AI翻译
  作者：Perry, Patrick O.
  作者单位：New York University
  摘要：Hierarchical models allow for heterogeneous behaviours in a population while simultaneously borrowing estimation strength across all subpopulations. Unfortunately, existing likelihood-based methods for fitting hierarchical models have high computational demands, and these demands have limited their adoption in large-scale prediction and inference problems. The paper proposes a moment-based procedure for estimating the parameters of a hierarchical model which has its roots in a method originall...
• Semiparametric dose finding methods AI翻译
  作者：Clertant, M.; O'Quigley, J.
  作者单位：Sorbonne Universite
  摘要：We describe a new class of dose finding methods to be used in early phase clinical trials. Under some added parametric conditions the class reduces to the family of continual reassessment method (CRM) designs. Under some relaxation of the underlying structure the method is equivalent to the cumulative cohort design, the modified toxicity probability interval method or Bayesian optimal interval design classes of methods, which are non-parametric in nature whereas the CRM class can be viewed as ...
• Global envelope tests for spatial processes AI翻译
  作者：Myllymaki, Mari; Mrkvicka, Tomas; Grabarnik, Pavel; Seijo, Henri; Hahn, Ute
  作者单位：Natural Resources Institute Finland (Luke); University of South Bohemia Ceske Budejovice; Russian Academy of Sciences; Pushchino Scientific Center for Biological Research (PSCBI) of the Russian Academy of Sciences; Institute of Physicohemical & Biological Problems of Soil Science; Aalto University; Aarhus University
  摘要：Envelope tests are a popular tool in spatial statistics, where they are used in goodness-of-fit testing. These tests graphically compare an empirical function T(r) with its simulated counterparts from the null model. However, the type I error probability is conventionally controlled for a fixed distance r only, whereas the functions are inspected on an interval of distances I. In this study, we propose two approaches related to Barnard's Monte Carlo test for building global envelope tests on I...
• On the exact region determined by Kendall's τ and Spearman's ρ AI翻译
  作者：Schreyer, Manuela; Paulin, Roland; Trutschnig, Wolfgang
  作者单位：Salzburg University
  摘要：Using properties of shuffles of copulas and tools from combinatorics we solve the open question about the exact region determined by all possible values of Kendall's and Spearman's . In particular, we prove that the well-known inequality established by Durbin and Stuart in 1951 is not sharp outside a countable set, give a simple analytic characterization of in terms of a continuous, strictly increasing piecewise concave function and show that is compact and simply connected, but not convex. Th...
• Modelling function-valued stochastic processes, with applications to fertility dynamics AI翻译
  作者：Chen, Kehui; Delicado, Pedro; Muller, Hans-Georg
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Universitat Politecnica de Catalunya; University of California System; University of California Davis
  摘要：We introduce a simple and interpretable model for functional data analysis for situations where the observations at each location are functional rather than scalar. This new approach is based on a tensor product representation of the function-valued process and utilizes eigenfunctions of marginal kernels. The resulting marginal principal components and product principal components are shown to have nice properties. Given a sample of independent realizations of the underlying function-valued st...