-
作者：Beran, R; Dümbgen, L
作者单位：University of California System; University of California Berkeley; Ruprecht Karls University Heidelberg
摘要：An unknown signal plus white noise is observed at n discrete time points. Within a large convex class of linear estimators of xi, we choose the estimator <(xi)over cap> that minimizes estimated quadratic risk. By construction, <(xi)over cap> is nonlinear. This estimation is done after orthogonal transformation of the data to a reasonable coordinate system. The procedure adaptively tapers the coefficients of the transformed data. If the class of candidate estimators satisfies a uniform entropy ...
-
作者：Dauxois, J; Nkiet, GM
作者单位：Centre National de la Recherche Scientifique (CNRS); Universite de Toulouse; Universite Toulouse III - Paul Sabatier
摘要：Measures of association between two random variables (r.v.) that are symmetric nondecreasing functions of the canonical coefficients provided by the nonlinear canonical analysis of the r.v.'s are studied. These measures can be used to characterize independence. Their estimators are obtained by estimating a suitable approximation to nonlinear canonical analysis. When some conditions ae satisfied, asymptotic distributions of the estimators, both under the independence hypothesis and under depend...
-
作者：Scheike, TH; Zhang, MJ
作者单位：University of Copenhagen; Medical College of Wisconsin
摘要：The longitudinal regression model Y-i,Y-j = m(V-tau i,j(i)) + epsilon(i,j) where Y-i,Y-j, is the jth measurement of the ith subject at random time tau(i,j), m is the regression function, V-tau i,j(i) is a predictable covariate process observed at time tau(i,j) and epsilon(i,j) is noise, often provides an adequate framework for modeling and comparing groups of data. The proposed longitudinal regression model is based on marked point process theory, and allows a quite general dependency structur...
-
作者：Cheng, CS; Mukerjee, R
作者单位：University of California System; University of California Berkeley; Indian Institute of Management (IIM System); Indian Institute of Management Calcutta
摘要：Using the approach of finite projective geometry, we make a systematic study of estimation capacity, a criterion of model robustness, under the absence of interactions involving three or more factors. Some general results, providing designs with maximum estimation capacity, are obtained. In particular, for two-level factorials, it is seen that constructing a design with maximum estimation capacity calls for choosing points from a finite projective geometry such that the number of lines is maxi...
-
作者：Chan, NH; Palma, W
作者单位：Carnegie Mellon University; Pontificia Universidad Catolica de Chile
摘要：This paper develops a state space modeling for long-range dependent data. Although a long-range dependent process has an infinite-dimensional state space representation, it is shown that by using the Kalman filter, the exact likelihood function can be computed recursively in a finite number of steps. Furthermore, an approximation to the likelihood function based on the truncated state space equation is considered. Asymptotic properties of these approximate maximum likelihood estimates are esta...
-
作者：Knight, K
作者单位：University of Toronto
摘要：It is well known that L-1-estimators of regression parameters are asymptotically normal if the distribution function has a positive derivative at 0. In this paper, we derive the asymptotic distributions under more general conditions on the behavior of the distribution function near 0.
-
作者：Ishwaran, H
作者单位：Cleveland Clinic Foundation
摘要：Advances in Markov chain Monte Carlo (MCMC) methods now make it computationally feasible and relatively straightforward to apply the Dirichlet process prior in a wide range of Bayesian nonparametric problems. The feasibility of these methods rests heavily on the fact that the MCMC approach avoids direct sampling of the Dirichlet process and is instead based on sampling the finite-dimensional posterior which is obtained from marginalizing out the process. In application, it is the integrated po...
-
作者：El Barmi, H; Dykstra, R
作者单位：Kansas State University; University of Iowa
摘要：The purpose of this article is to derive and illustrate a method for fitting models involving both convex and log-convex constraints on the probability vector(s) of a (product) multinomial distribution. We give a two-step algorithm to obtain maximum likelihood estimates of the probability vector(s) and show that it is guaranteed to converge to the true solution. Some examples are discussed which illustrate the procedure.
-
作者：Dette, H; Munk, A
作者单位：Ruhr University Bochum
摘要：A new test is proposed in order to verify that a regression function, say g, has a prescribed (Linear) parametric form. This procedure is based on the large sample behavior of an empirical L-2-distance between g and the subspace U spanned by the regression functions to be verified. The asymptotic distribution of the test statistic is shown to be normal with parameters depending only on the variance of the observations and the L-2-distance between the regression function g and the model space U...
-
作者：van der Laan, MJ; McKeague, IW
作者单位：University of California System; University of California Berkeley; State University System of Florida; Florida State University
摘要：The Kaplan-Meier estimator of a survival function is well known to be asymptotically efficient when cause of failure is always observed. It has been an open problem, however, to find an efficient estimator when failure indicators are missing at random. Lo showed that nonparametric maximum likelihood estimators are inconsistent, and this has led to several proposals of ad hoc estimators, none of which are efficient. We now introduce a sieved nonparametric maximum likelihood estimator, and show ...
