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作者：GAJEK, L; KALUSZKA, M
作者单位：Polish Academy of Sciences
摘要：The problem of Bayes estimation of the scale parameter is considered. Lower bounds for the asymptotic Bayes risk are given as the restricted parameter space increases to the positive half-line. The results are next applied to establish the second-order minimax estimator of the scale parameter. Surprisingly, the least favorable distribution coincides with that for the corresponding location parameter problem.
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作者：IOANNIDIS, EE
作者单位：Ruprecht Karls University Heidelberg
摘要：In this paper we propose a Capon-type estimator for the spectrum of a stationary time series. This estimator may be viewed as an alternative to classical periodogram-based estimators. Its advantage is that it copes with the ''leakage effect'' by using implicitly automatic adaptive windowing. We show its asymptotic equivalence to a random variable which is a quadratic form in the observations, thus obtaining the asymptotic normality of the Capon estimator. We also study its asymptotic bias and ...
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作者：HOSSJER, O; ROUSSEEUW, PJ; CROUX, C
摘要：The influence function is determined for (twice) repeated median estimators with arbitrary kernel functions, and more generally in the case where the two medians are replaced by a general class of estimators. Asymptotic normality is then established for the repeated median estimator of the slope parameter in simple linear regression. In this case the influence function is hounded. For bivariate Gaussian data the efficiency becomes 4/pi(2) approximate to 40.5%, which is the square of the effici...
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作者：BAI, JS
摘要：This paper studies the weak convergence of the sequential empirical process (K) over cap(n), of the estimated residuals in ARMA(p, q) models when the errors are independent and identically distributed. It is shown that, under some mild conditions, (K) over cap(n), converges weakly to a Kiefer process. The weak convergence is discussed for both finite and infinite variance time series models. An application to a change-point problem is considered.
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作者：WEISBERG, S; WELSH, AH
作者单位：Australian National University; Australian National University
摘要：We consider the fitting of generalized linear models in which the link function is assumed to be unknown, and propose the following computational method: First, estimate regression coefficients using the canonical link. Then, estimate the link via a kernel smoother, treating the direction in the predictor space determined by the regression coefficients as known. Then reestimate the direction using the estimated link and alternate between these two steps. We show that under fairly general condi...
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作者：AKRITAS, MG
摘要：We consider the problem of estimating the bivariate distribution of the random vector (X, Y) when Y may be subject to random censoring. The censoring variable C is allowed to depend on X but it is assumed that Y and C are conditionally independent given X = x. The estimate of the bivariate distribution is obtained by averaging estimates of the conditional distribution of Y given X = x over a range of values of x. The weak convergence of the centered estimator multiplied by n(1/2) is obtained, ...
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作者：HWANG, JTG; DASPEDDADA, S
作者单位：University of Virginia
摘要：This article deals with the construction of confidence intervals when the components of the location parameter mu of the random variable X, which is elliptically symmetrically distributed, are subject to order restrictions. Several domination results are proved by studying the derivative of the coverage probability of the confidence intervals centered at the improved point estimators. Consequently, we strengthen the previously known results regarding the simple ordering and obtain several new ...
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作者：LAVINE, M
摘要：The definition and elementary properties of Polya tree distributions are reviewed. Two theorems are presented showing that Polya trees can be constructed to concentrate arbitrarily closely about any desired pdf, and that Polya tree priors can put positive mass in every relative entropy neighborhood of every positive density with finite entropy, thereby satisfying a consistency condition. Such theorems are false for Dirichlet processes. Models are constructed combining partially specified Polya...
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作者：BUHLMANN, P
摘要：We apply the bootstrap for general stationary observations, proposed by Kunsch, to the empirical process for p-dimensional random vectors. It is known that the empirical process in the multivariate case converges weakly to a certain Gaussian process. We show that the bootstrapped empirical process converges weakly to the same Gaussian process almost surely assuming that the block length l for constructing bootstrap replicates satisfies l(n) = O(n(1/2 -epsilon) ), 0 < epsilon < 1/2, and l(n) --...
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作者：NAIKNIMBALKAR, UV; RAJARSHI, MB
摘要：We show that the empirical process of the block-based bootstrap observations from a stationary sequence converges weakly to an appropriate Gaussian process, conditionally in probability and almost surely depending upon the block length. This bootstrap was introduced by Kunsch and later by Liu and Singh. Applications in estimation of the sampling distribution of a compactly differentiable functional are indicated.
