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作者：HORVATH, L
摘要：We compute the asymptotic distribution of the maximum likelihood ratio test when we want to check whether the parameters of normal observations have changed at an unknown point. The proof is based on the limit distribution of the largest deviation between a d-dimensional Ornstein-Uhlenbeck process and the origin.
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作者：EVANS, SN; SPEED, TP
摘要：The so-called method of invariants is a technique in the field of molecular evolution for inferring phylogenetic relations among a number of species on the basis of nucleotide sequence data. An invariant is a polynomial function of the probability distribution defined by a stochastic model for the observed nucleotide sequence. This function has the special property that it is identically zero for one possible phylogeny and typically nonzero for another possible phylogeny. Thus it is possible t...
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作者：PUKELSHEIM, F; STUDDEN, WJ
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Purdue University System; Purdue University
摘要：E-optimal designs for the full mean parameter vector, and for many subsets in univariate polynomial regression models are determined. The derivation is based on the interplay between E-optimality and scalar optimality. The scalar parameter systems are obtained as transformations of the coefficient vector c of the Chebyshev polynomial.
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作者：VANDEGEER, S
摘要：Consider a class P = {P(theta) : theta is-an-element-of THETA} of probability measures on a measurable space (K, A), dominated by a sigma-finite measure mu. Let f(theta) = dP(theta)/dmu, theta is-an-element-of THETA, and let theta(n) be a maximum likelihood estimator based on n independent observations from P(theta0), theta0 is-an-element-of THETA). We use results from empirical process theory to obtain convergence for the Hellinger distance h(f(thetan), f(theta0)), under certain entropy condi...
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作者：SASIENI, P
摘要：New estimators for Cox regression are considered. Their asymptotic properties, both on and off the model, are established. Corollaries include conditions under which the maximum partial likelihood estimator defines a parameter in the population and the asymptotics of the case-cohort estimator. Robust estimators that minimize the asymptotic variance subject to a bound on the maximal bias on infinitesimal neighborhoods are discussed. The estimators are illustrated with medical data.
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作者：BOOTH, JG; HALL, P
作者单位：Australian National University; Commonwealth Scientific & Industrial Research Organisation (CSIRO)
摘要：In a recent paper, C. F. J. Wu showed that the jackknife estimator of a distribution function has optimal convergence rate O(n-1/2), where n denotes the sample size. This rate is achieved by retaining O(n) data values from the original sample during the jackknife algorithm. Wu's result is particularly important since it permits a direct comparison of jackknife and bootstrap methods for distribution estimation. In the present paper we show that a very simple, nonempirical modification of the ja...
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作者：GU, C; QIU, CF
摘要：In this article, a class of penalized likelihood probability density estimators is proposed and studied. The true log density is assumed to be a member of a reproducing kernel Hilbert space on a finite domain, not necessarily univariate, and the estimator is defined as the unique unconstrained minimizer of a penalized log likelihood functional in such a space. Under mild conditions, the existence of the estimator and the rate of convergence of the estimator in terms of the symmetrized Kullback...
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作者：HUSKOVA, M; JANSSEN, P
作者单位：Hasselt University
摘要：A generalized bootstrap version is defined for degenerate U-statistics. Our main result shows that the (conditional) distribution function of the bootstrapped degenerate U-statistic provides a consistent estimator for the unknown distribution function of the degenerate U-statistic under consideration. For the proof we rely on a rank statistic approach.
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作者：BOOTH, JG; HALL, P
作者单位：Australian National University
摘要：We suggest bootstrap methods for constructing confidence bands (and intervals) for an unknown linear functional relationship in an errors-invariables model. It is assumed that the ratio of error variances is known to lie within an interval LAMBDA = [lambda1, lambda2]. A confidence band is constructed for the range of possible linear relationships when lambda is-an-element-of LAMBDA. Meaningful results are obtained even in the extreme case LAMBDA = [0, infinity], which corresponds to no assumpt...
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作者：DIACONIS, P; FREEDMAN, DA
作者单位：University of California System; University of California Berkeley
摘要：The performance of Bayes estimates are studied, under an assumption of conditional exchangeability. More exactly, for each subject in a data set, let xi be a vector of binary covariates and let eta be a binary response variable, with P{eta = 1\xi} = f(xi). Here, f is an unknown function to be estimated from the data; the subjects are independent, and satisfy a natural ''balance'' condition. Define a prior distribution on f as SIGMA(k)omega(k)pi(k)/SIGMA(k)omega(k), where pi(k) is uniform on th...
