1996

最新文章

• 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 ...
• Likelihood and linkage: From Fisher to the future AI翻译
  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...
• Heuristics of instability and stabilization in model selection AI翻译
  作者：Breiman, L
  摘要：In model selection, usually a ''best'' predictor is chosen from a collection {<(mu)over cap>(., s)} of predictors where <(mu)over cap>(., s) is the minimum least-squares predictor in a collection U-s of predictors. Here s is a complexity parameter; that is, the smaller s, the lower dimensional/smoother the models in U-s. If L is the data used to derive the sequence {<(mu)over cap>(., s)}, the procedure is called unstable if a small change in L can cause large changes in {<(mu)over cap>(., s)}....
• A large deviation theorem for the q-sample likelihood ratio statistic AI翻译
  作者：Rublik, F
  摘要：An upper bound for the tail probability P-theta(log(L(x((n1,...,nq)),Theta)/ L(x((n1,...,nq)),theta) greater than or equal to t) is derived in the case of sampling from q populations. This estimate is used for establishing the Hodges-Lehmann optimality of a test statistic for a hypothesis on exponential distributions.
• Maximum likelihood estimation under a spatial sampling scheme AI翻译
  作者：vanderVaart, A
  摘要：It is shown that the maximum likelihood estimator in a model used in the statistical analysis of computer experiments is asymptotically efficient.
• 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...
• Exponential empirical likelihood is not Bartlett correctable AI翻译
  作者：Jing, BY; Wood, ATA
  作者单位：Australian National University
  摘要：In a recent paper, DiCiccio, Hall and Romano established that Owen's empirical likelihood is Bartlett correctable. This is an intriguing and perhaps surprising result and is the only nonparametric context in which Bartlett correctability is known to hold. An alternative, closely related nonparametric likelihood, referred to here as exponential empirical likelihood, may be constructed using Efron's method of nonparametric tilting. The purpose of this note is to show that exponential empirical l...
• On the asymptotic properties of a flexible hazard estimator AI翻译
  作者：Strawderman, RL; Tsiatis, AA
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health
  摘要：Suppose one has a stochastic time-dependent covariate Z(t), and is interested in estimating the hazard relationship lambda(t\(Z) over bar(t)) = omega(Z(t)), where (Z) over bar(t) denotes the history of Z(t) up to and including time t. In this paper, we consider a model of the form exp(s(n)(Z(t))), where s(n)(Z(t)) is a spline of finite but arbitrary order, and investigate the behavior of the maximum likelihood estimator of the hazard as the number of knots in the spline function increases with...
• An information inequality for the Bayes risk AI翻译
  作者：Sato, M; Akahira, M
  摘要：This paper presents a lower bound, derived from the information inequality for the Bayes risk with respect to truncated priors under quadratic loss. It is discussed in cases where the regularity condition of Brown and Gajek is not always satisfied. A related result for the minimax risk is also given.