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最新文章

• Nonparametric quasi-likelihood AI翻译
  作者：Chiou, JM; Müller, HG
  作者单位：National Chung Cheng University; University of California System; University of California Davis
  摘要：The quasi-likelihood function proposed by Wedderburn broadened the scope of generalized linear models by specifying the variance function instead of the entire distribution. However, complete specification of variance functions in the quasi-likelihood approach may not be realistic We define a nonparametric quasi-likelihood by replacing the specified variance function in the conventional quasi-likelihood with a nonparametric variance function estimate. This nonparametric variance function estim...
• Limits to classification and regression estimation from ergodic processes AI翻译
  作者：Nobel, AB
  作者单位：University of North Carolina; University of North Carolina Chapel Hill
  摘要：We answer two open questions concerning the existence of universal schemes for classification and regression estimation from stationary ergodic processes. It is shown that no measurable procedure can produce weakly consistent regression estimates from every bivariate stationary ergodic process, even if the covariate and response variables are restricted to take values in the unit interval. It is further shown that no measurable procedure can produce weakly consistent 'classification rules from...
• Convergence of a stochastic approximation version of the EM algorithm AI翻译
  作者：Delyon, B; Lavielle, V; Moulines, E
  作者单位：Inria; Universite Paris Cite; Universite Paris Saclay; Centre National de la Recherche Scientifique (CNRS); Centre National de la Recherche Scientifique (CNRS)
  摘要：The expectation-maximization (EM) algorithm isa powerful computational technique for locating maxima of functions. It is widely used in statistics for maximum likelihood or maximum a posteriori estimation in incomplete data models. In certain situations, however, this method is not applicable because the expectation step cannot be performed in closed form. To deal with these problems, a novel method is introduced, the stochastic approximation EM (SAEM), which replaces the expectation step of t...
• On the multivariate runs test AI翻译
  作者：Henze, N; Penrose, MD
  作者单位：Helmholtz Association; Karlsruhe Institute of Technology; Durham University
  摘要：For independent d-variate random variables X-1,...,X-m with common density f and Y-1,...; Y-n with common density g, let R-m,R-n be the number of edges in the minimal spanning tree with vertices X-1,..., X-m, Y-1,...,Y-n that connect points from different samples. Friedman and Rafsky conjectured that a test of H-o: f = g that rejects H-o for small values of R-m,R-n should have power against general alternatives. We prove that R-m,R-n is asymptotically distribution-free under H-o, and that the ...
• Nonparametric model checks for time series AI翻译
  作者：Koul, HL; Stute, W
  作者单位：Michigan State University; Justus Liebig University Giessen
  摘要：This paper studies a class of tests useful for testing the goodness-of-fit of an autoregressive model. These tests are based on a class of empirical processes marked by certain residuals. The paper first gives their large sample behavior under null hypotheses. Then a martingale transformation of the underlying process is given that makes tests based on it asymptotically distribution free. Consistency of these tests is also discussed briefly.
• Posterior consistency of Dirichlet mixtures in density estimation AI翻译
  作者：Ghosal, S; Ghosh, JK; Ramamoorthi, RV
  作者单位：Vrije Universiteit Amsterdam; Indian Statistical Institute; Indian Statistical Institute Kolkata; Michigan State University; Purdue University System; Purdue University
  摘要：A Dirichlet mixture of normal densities is a useful choice for a prior distribution on densities in the problem of Bayesian density estimation. In the recent years, efficient Markov chain Monte Carlo method for the computation of the posterior distribution has been developed. The method has been applied to data arising from different fields of interest. The important issue of consistency was however left open. In this paper, we settle this issue in affirmative.
• Exploring interactions in high-dimensional tables: A bootstrap alternative to log-linear models AI翻译
  作者：Streitberg, B
  作者单位：University of Hamburg
  摘要：Based on a revised Lancaster-type representation of the additive interactions associated with a probability measure, a new approach for the analysis of high-dimensional contingency tables is proposed. The approach is essentially model-free because the additive interaction tensor is merely a convenient reparameterization of the given table. Single interaction terms are investigated using the bootstrap method whose first-order asymptotic validity is immediate. The global structure can be investi...
• On residual empirical processes of stochastic regression models with applications to time series AI翻译
  作者：Lee, S; Wei, CZ
  作者单位：Seoul National University (SNU); Academia Sinica - Taiwan
  摘要：Motivated by Gaussian tests for a time series, we are led to investigate the asymptotic behavior of the residual empirical processes of stochastic regression models. These models cover the fixed design regression models as well as general AR(q) models. Since the number of the regression coefficients is allowed to grow as the sample size increases, the obtained results are also applicable to nonlinear regression and stationary AR(infinity) models. In this paper, we first derive an oscillation-l...
• Eaton's Markov chain, its conjugate partner and P-admissibility AI翻译
  作者：Hobert, JP; Robert, CP
  作者单位：State University System of Florida; University of Florida; Institut Polytechnique de Paris; ENSAE Paris
  摘要：Suppose that X is a random variable with density f(x\theta) and that pi(theta\x) is a proper posterior corresponding to an improper prior nu(theta). The prior is called P-admissible if the generalized Bayes estimator of every bounded function of theta is almost-nu-admissible under squared error loss. Eaten showed that recurrence of the Markov chain with transition density R(eta\theta) = integral pi(eta\x)f(x\theta) dx is a sufficient condition for P-admissibility of nu(theta). We show that Eat...
• Discontinuous versus smooth regression AI翻译
  作者：Müller, HG; Stadtmüller, U
  作者单位：University of California System; University of California Davis; Ulm University
  摘要：Given measurements (x(i), y(i)), i = 1,..., n, we discuss methods to assess whether an underlying regression function is smooth (continuous or differentiable) or whether it has discontinuities. The variance of the measurements is assumed to be unknown, and is estimated simultaneously. By regressing squared differences of the data formed with various span sizes on the span size itself, we obtain an asymptotic linear model with dependent errors. The parameters of this asymptotic linear model inc...