4期

最新文章

• Locally parametric nonparametric density estimation AI翻译
  作者：Hjort, NL; Jones, MC
  作者单位：Open University - UK
  摘要：This paper develops a nonparametric density estimator with parametric overtones. Suppose f(x, theta) is some family of densities, indexed by a vector of parameters theta. We define a local kernel-smoothed likelihood function which, for each x, can be used to estimate the best local parametric approximant to the true density. This leads to a new density estimator of the form f(x, <(theta)over cap (x)>), thus inserting the best local parameter estimate for each new value of x. When the bandwidth...
• On the asymptotic performance of median smoothers in image analysis and nonparametric regression AI翻译
  作者：Koch, I
  摘要：For d-dimensional images and regression functions the true object is estimated by median smoothing. The mean square Error of the median smoother is calculated using the framework of M-estimation, and an expression for the asymptotic rate of convergence of the mean square error is given. It is shown that the median smoother performs asymptotically as well as the local mean. The optimal window size and the bandwidth of the median smoother are given in terms of the sample sire and the dimension o...
• Uniform rates of estimation in the semiparametric Weibull mixture model AI翻译
  作者：Ishwaran, HZ
  摘要：This paper presents a uniform estimator for a finite-dimensional parameter in the semiparametric Weibull mixture model. The rates achieved hv the estimator hold uniformly over shrinking sequences of models much more general than traditional sequences that are required to satisfy a Hellinger differentiable property. We show that these rates are optimal in a class of identified models constrained by a moment condition on the nonparametric mixing distribution.
• The 2d+4 simple quadratic natural exponential families on R(d) AI翻译
  作者：Casalis, M
  摘要：The present paper describes all the natural exponential families on R(d) whose variance function is of the form V(m) = am x m + B(m) + C, with m x m[theta] = [theta,m]m and B tinear in m. There are 2d + 4 types of such families, which are built from particular mixtures of families of Normal, Poisson, gamma, hyperbolic on R and (negative-) multinomial distributions. The proof of this result relies mainly on techniques used in the elementary theory of Lie algebras.
• Asymptotically honest confidence sets for structural errors-in-variables models AI翻译
  作者：Huwang, L
  作者单位：Cornell University
  摘要：The problem of constructing confidence sets for the structural errors-in-variables model is considered under the assumption that the variance of the error associated with the covariate is known. Previously proposed confidence sets for this model suffer from the problem that they all have zero confidence levels for any sample size, where the confidence level of a confidence set is defined to be the infimum of coverage probability over the parameter space. In this paper we construct some asympto...
• Regression rank scores estimation in ANOCOVA AI翻译
  作者：Sen, PK
  作者单位：University of North Carolina; University of North Carolina Chapel Hill
  摘要：In semiparametric ANOCOVA (mixed-effects) models, the role of regression rank scores in robust estimation of fixed-effects parameters as well as covariate regression functionals is critically appraised, and the relevant asymptotic theory is presented.
• On the dimension of the boundary of clumps in a multi-type Boolean model AI翻译
  作者：Hall, P; Polzehl, J
  作者单位：Commonwealth Scientific & Industrial Research Organisation (CSIRO); Zuse Institute Berlin
  摘要：In a fascinating article on models for particulate microstructure, Hermann and Ohser argue that the superposition of stochastically independent Boolean models may be thought of as producing sets whose boundaries have unusual properties of dimension. Hermann and Ohser employ such superposition models to analyse the particulate structure of rust. In the present paper we provide a theoretical foundation for their work, with respect to both the definition of dimension and its statistical estimatio...
• Asymptotic theory for nonparametric estimation of survival curves under order restrictions AI翻译
  作者：Praestgaard, JT; Huang, J
  作者单位：University of Iowa
  摘要：We consider two problems in nonparametric survival analysis under the restriction of stochastic ordering. The first problem is that of estimating a survival function <(F)over bar (t)> under the restriction <(F)over bar (t)> greater than or equal to <(F)over bar (0)(t)>, all t, where (F) over bar (0)(t) is known. The second problem consists of estimating two unknown survival functions <(F)over bar ((t))(t)> and <(F)over bar ((2))(t)> when it is known that <(F)over bar ((1))(t)> greater than or ...
• On the determinant of the second derivative of a Laplace transform AI翻译
  作者：Kokonendji, CC; Seshadri, V
  作者单位：McGill University; Universite de Toulouse; Universite Toulouse III - Paul Sabatier
  摘要：If Ct is a positive measure on R(n) with Laplace transform L(mu), we show that there exists a positive measure v on R(n) such that det L(mu)(n) = L(v). We deduce various corollaries from this result and, in particular, we obtain the Rao-Blackwell estimator of the determinant of the variance of a natural exponential family on R(n) based on (n + 1) observations. A new proof and extensions of Lindsay's results on the determinants of moment matrices are also given. Finally we give a characterizati...
• Change point estimation using nonparametric regression AI翻译
  作者：Loader, CR
  摘要：We consider a regression model in which the mean function may have a discontinuity at an unknown point. We propose an estimate of the location of the discontinuity based on one-side nonparametric regression estimates of the mean function. The change point estimate is shown to converge in probability at rate O(n(-1)) and to have the same asymptotic distribution as maximum Likelihood estimates considered by other authors under parametric regression models. Confidence regions for the location and...