2003

最新文章

• SPRT and CUSUM in hidden Markov models AI翻译
  作者：Fuh, CD
  作者单位：Academia Sinica - Taiwan
  摘要：In this paper, we study the problems of sequential probability ratio tests for parameterized hidden Markov models. We investigate in some detail the performance of the tests and derive corrected Brownian approximations for error probabilities and expected sample sizes. Asymptotic optimality of the sequential probability ratio test for testing simple hypotheses based on hidden Markov chain data is established. Next, we consider the cumulative sum (CUSUM) procedure for change point detection in ...
• Large sample theory of intrinsic and extrinsic sample means on manifolds. I AI翻译
  作者：Bhattacharya, R; Patrangenaru, V
  作者单位：Indiana University System; Indiana University Bloomington; University System of Georgia; Georgia State University
  摘要：Sufficient conditions are given for the uniqueness of intrinsic and extrinsic means as measures of location of probability measures Q on Riemannian manifolds. It is shown that, when uniquely defined, these are estimated consistently by the corresponding indices of the empirical (Q) over cap (n). Asymptotic distributions of extrinsic sample means are derived. Explicit computations of these indices of (Q) over cap (n) and their asymptotic dispersions are carried out for distributions on the sphe...
• Nonparametric estimation of convex models via mixtures AI翻译
  作者：Hoff, PD
  作者单位：University of Washington; University of Washington Seattle
  摘要：We present a general approach to estimating probability measures constrained to lie in a convex set. We represent constrained measures as mixtures of simple, known extreme measures, and so the problem of estimating a constrained measure becomes one of estimating an unconstrained mixing measure. Convex constraints arise in many modeling situations, such as estimation of the mean and estimation under stochastic ordering constraints. We describe mixture representation techniques for these and oth...
• Stochastic approximation AI翻译
  作者：Lai, TL
  作者单位：Stanford University
  摘要：Stochastic approximation, introduced by Robbins and Monro in 1951, has become an important and vibrant subject in optimization, control and signal processing. This paper reviews Robbins' contributions to stochastic approximation and gives an overview of several related developments.
• On adaptive estimation in nonstationary ARMA models with Garch errors AI翻译
  作者：Ling, SQ; McAleer, M
  作者单位：Hong Kong University of Science & Technology; University of Western Australia
  摘要：This paper considers adaptive estimation in nonstationary autoregressive moving average models with the noise sequence satisfying a generalized autoregressive conditional heteroscedastic process. The locally asymptotic quadratic form of the log-likelihood ratio for the model is obtained. It is shown that the limit experiment is neither LAN nor LAMN, but is instead LABF. For the model with symmetric density of the rescaled error, a new efficiency criterion is established for a class of defined ...
• Image denoising: Pointwise adaptive approach AI翻译
  作者：Polzehl, J; Spokoiny, V
  作者单位：Leibniz Association; Weierstrass Institute for Applied Analysis & Stochastics
  摘要：A new method of pointwise adaptation has been proposed and studied in Spokoiny [(1998) Ann. Statist. 26 1356-1378] in the context of estimation of piecewise smooth univariate functions. The present paper extends that method to estimation of bivariate grey-scale images composed of large homogeneous regions with smooth edges and observed with noise on a gridded design. The proposed estimator (f) over cap (x) at a point x is simply the average of observations over a window (U) over cap (x) select...