2期

最新文章

• AN OMNIBUS TEST FOR INDEPENDENCE OF A SURVIVAL-TIME FROM A COVARIATE AI翻译
  作者：MCKEAGUE, IW; NIKABADZE, AM; SUN, YQ
  作者单位：University of Rochester
  摘要：It has been over 60 years since Kolmogorov introduced a distribution-free omnibus test for the simple null hypothesis that a distribution function coincides with a given distribution function. Doob subsequently observed that Kolmogorov's approach could be simplified by transforming the empirical process to an empirical process based on uniform random variables. Recent use of more sophisticated transformations has led, to the construction of asymptotically distribution-free omnibus tests when u...
• ESTIMATING THE REAL PARAMETER IN A 2-SAMPLE PROPORTIONAL ODDS MODEL AI翻译
  作者：WU, CO
  摘要：This paper considers efficient estimation of the Euclidean parameter theta in the proportional odds model G(1 - G)(-1) = theta F(1 - F)(-1) when two independent i.i.d. samples with distributions F and G, respectively, are observed. The Fisher information I(theta) is calculated based on the solution of a pair of integral equations which are derived from a class of more general semiparametric models. A one-step estimate is constructed using an initial root N-consistent estimate and shown to be a...
• ESTIMATION OF A LOSS FUNCTION FOR SPHERICALLY SYMMETRICAL DISTRIBUTIONS IN THE GENERAL LINEAR-MODEL AI翻译
  作者：FOURDRINIER, D; WELLS, MT
  作者单位：Cornell University
  摘要：This paper is concerned with estimating the loss of a point estimator when sampling from a spherically symmetric distribution. We examine the canonical setting of a general linear model where the dimension of the parameter space is greater than 4 and less than the dimension of the sampling space. We consider two location estimators-the least squares estimator and a shrinkage estimator-and we compare their unbiased loss estimator with an improved loss estimator. The domination results are valid...
• THE CENTRAL-LIMIT-THEOREM UNDER RANDOM CENSORSHIP AI翻译
  作者：STUTE, W
  摘要：Let ($) over cap F-n be the Kaplan-Meier estimator of a distribution function F computed from randomly censored data. We show that under optimal integrability assumptions on a function phi, the Kaplan-Meier integral integral phi d ($) over cap F-n, when properly standardized, is asymptotically normal.
• EFFICIENT ESTIMATION OF MONOTONE BOUNDARIES AI翻译
  作者：KOROSTELEV, AP; SIMAR, L; TSYBAKOV, AB
  作者单位：Universite Catholique Louvain; Sorbonne Universite
  摘要：Let g: [0,1] --> [0,1] be a monotone nondecreasing function and let G be the closure of the set {(x, y) is an element of [0,1] X [0,1]: 0 less than or equal to y less than or equal to g(x)}. We consider the problem of estimating the set G from a sample of i.i.d. observations uniformly distributed in G. The estimation error is measured in the Hausdorff metric. We propose the estimator which is asymptotically efficient in the minimax sense.
• ESTIMATING THE NUMBER OF PEAKS IN A RANDOM-FIELD USING THE HADWIGER CHARACTERISTIC OF EXCURSION SETS, WITH APPLICATIONS TO MEDICAL IMAGES AI翻译
  作者：WORSLEY, KJ
  摘要：Certain three-dimensional images arising in medicine and astrophysics are modelled as a smooth random field, and experimenters are interested in the number of peaks or ''hot-spots'' present in such an image. This paper studies the Hadwiger characteristic of the excursion set of a random field. The excursion set is the set of points where the image exceeds a fixed threshold, and the Hadwiger characteristic, like the Euler characteristic, counts the number of connected components in the excursio...
• ADMISSIBILITY AND MINIMAXITY OF THE UMVU ESTIMATOR OF P(X-LESS-THAN-Y) AI翻译
  作者：YU, QQ; GOVINDARAJULU, Z
  作者单位：University of Kentucky
  摘要：Suppose that X(1),...,X(m) are i.i.d. from a continuous distribution function F and Y-1,...,Y-n are i.i.d. from a continuous distribution function G; X's and Y's are independent. A minimum variance unbiased estimator of P(X < Y) is the Mann-Whitney statistic. We show that the Mann-Whitney statistic is admissible under a class of weighted squared error losses and is minimax under a proper weighted squared error loss.
• UNIFORM COVERAGE BOUNDS FOR CONFIDENCE-INTERVALS AND BERRY-ESSEEN THEOREMS FOR EDGEWORTH EXPANSION AI翻译
  作者：HALL, P; JING, BY
  摘要：We derive upper bounds for the coverage error of confidence intervals for a population mean uniformly over large classes of populations and different types of confidence intervals. It is shown that the order of these bounds is achieved by the normal approximation method for constructing confidence intervals, uniformly over distributions with finite third moment, and, by an empirical Edgeworth correction of this approach, uniformly over smooth distributions with finite fourth moments. These res...
• A NOTE ON ADMISSIBILITY WHEN PRECISION IS UNBOUNDED AI翻译
  作者：ANDERSON, C; PAL, N
  摘要：The estimation of a common mean vector theta given two independent normal observations X similar to N-p(theta, rho(x)(2)I) and Y similar to N-p(theta, rho(y)(2)I) is reconsidered. It being known that the estimator eta X + (1 - eta)Y is inadmissible when eta is an element of (0,1), we show that when eta is 0 or 1, then the opposite is true, that is, the estimator is admissible. The general situation is that an estimator X* can be improved by shrinkage when there exists a statistic B which, in a...
• AUTOREGRESSION QUANTILES AND RELATED RANK-SCORES PROCESSES AI翻译
  作者：KOUL, HL; SALEH, AKME
  作者单位：Carleton University
  摘要：This paper develops extensions of the regression quantiles of Koenker and Bassett (1978) to autoregression. It generalizes several results of Jureckova (1992a) and Gutenbrunner and Jureckova (1992) in linear regression to autoregression models. In particular, it gives the asymptotic uniform linearity of linear rank-scores statistics based on residuals suitable in autoregression. It also discusses the two types of L-statistics appropriate in autoregression.