-
作者：Chen, K; Ying, ZL
作者单位：Rutgers University System; Rutgers University New Brunswick
摘要：Hall and Wellner proposed a natural extension of the Kolmogorov-Slmirnov simultaneous confidence band for survival curve using the Kaplan-Meier estimator. They and Gill conjectured that the confidence band holds for all t up to the last observed failure time. A counterexample is given herein, showing that this may not always be true.
-
作者：Wang, ZM; Gardiner, JC
摘要：A model of interval censorship of a failure time T is considered when there is only one inspection time Y. The observable data are n independent copies of the pair (Y, delta), where delta = [T less than or equal to Y]. We construct a class of self-consistent estimators of the survival function of T defined implicitly through two equations and show their strong consistency under certain conditions. The properties of the nonparametric maximum likelihood estimator are also investigated.
-
作者：Thompson, EA
摘要：Genetic epidemiology is almost unique among the sciences in that computation of a likelihood function is the accepted approach to statistical inference. In the context of genetic linkage analysis, in which genes are mapped by analysing the dependence in inheritance of different traits, the use of likelihood dates back to the early work of Fisher and Haldane, and has seldom been seriously challenged. After introducing the underlying genetic concepts, this paper reviews the history of the statis...
-
作者：Chen, K; Lo, SH
作者单位：Columbia University
摘要：In survival analysis with censored data, we consider three closely related survival function estimators: the Kaplan-Meier, Nelson and moment estimators. We derive the Edgeworth expansions for these three estimators with Studentization. Edgeworth expansions for the corresponding bootstrap statistics are also given. It is found that the bootstrap approximation is better than the normal approximation for the Studentized Kaplan-Meier and Nelson estimators, but not so for the Studentized moment est...
-
作者：Choi, SS; Hall, WJ; Schick, A
作者单位：University of Rochester; State University of New York (SUNY) System; Binghamton University, SUNY
摘要：Tests of hypotheses about finite-dimensional parameters in a semiparametric model are studied from Pitman's moving alternative (or local) approach using Le Cam's local asymptotic normality concept. For the case of a real parameter being tested, asymptotically uniformly most powerful (AUMP) tests are characterized for one-sided hypotheses, and AUMP unbiased tests for two-sided ones. An asymptotic invariance principle is introduced for multidimensional hypotheses, and AUMP invariant tests are ch...
-
作者：VanderVaart, A
摘要：We consider maximum likelihood estimation in several examples of semiparametric mixture models, including the exponential frailty model and the errors-in-variables model. The observations consist of a sample of size n from the mixture density integral p(theta)(x\z)d eta(z). The mixing distribution is completely unknown. We show that the first component <(theta(n))over tilde> of the joint maximum likelihood estimator (<(theta(n))over tilde>, <(eta(n))over tilde>) is asymptotically normal and as...
-
作者：Laurent, B
摘要：We consider the problem of estimating a functional of a density of the type integral phi(f,.). Starting from efficient estimators of linear and quadratic functionals of f and using a Taylor expansion of phi, we build estimators that achieve the n(-1/2) rate whenever if is smooth enough. Moreover, we show that these estimators are efficient. Concerning the estimation of quadratic functionals (more precisely, of integrated squared density) Bickel and Ritov have already built efficient estimators...
-
作者：Mathew, T; Zha, WX
摘要：In the multivariate calibration problem using a multivariate linear model, some conservative confidence regions are constructed. The regions are nonempty and invariant under nonsingular transformations. Situations where the explanatory variable occurs nonlinearly in the model are also considered. Computational aspects of the confidence region and its practical implementation are discussed. The results are illustrated using two examples. The examples show that our confidence regions are much mo...
-
作者：Sun, L
摘要：A two-way multivariate normal model is proposed and attention is focused on estimation of the mean values when the common variance of the observations is unknown. A class of empirical Bayes estimators is proposed and mean-squared errors are given. A lower bound on the mean-squared error is found and related to risk asymptotics. A James-Stein-type estimator is derived and compared with its competitor-a modal estimator that is obtained from a hierarchical prior for the unknown parameters.
-
作者：Wang, YZ
摘要：In this article we study function estimation via wavelet shrinkage for data with long-range dependence. We propose a fractional Gaussian noise model to approximate nonparametric regression with long-range dependence and establish asymptotics for minimax risks. Because of long-range dependence, the minimax risk and the minimax linear risk converge to 0 at rates that differ from those for data with independence or short-range dependence. Wavelet estimates with best selection of resolution level-...
