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作者：BERGER, JO; BROWN, LD; WOLPERT, RL
作者单位：University of Pennsylvania; Duke University
摘要：Preexperimental frequentist error probabilities are arguably inadequate, as summaries of evidence from data, in many hypothesis-testing settings. The conditional frequentist may respond to this by identifying certain subsets of the outcome space and reporting a conditional error probability, given the subset of the outcome space in which the observed data lie. Statistical methods consistent with the likelihood principle, including Bayesian methods, avoid the problem by a more extreme form of c...
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作者：COHEN, A; KEMPERMAN, JHB; SACKROWITZ, HB
摘要：Let (X(ij), z(i)), i = 1, 2, ..., k, j = 1, 2,..., n(i), be independent observations such that z(i) is a fixed r x 1 vector [r can be 0 (no z's observed) or 1, 2, ..., k - 1], and X(ij) is distributed according to a one-parameter exponential family which is log concave with natural parameter theta(i). We test the hypothesis that theta = Z beta, where theta = (theta(1), ..., theta(k))', Z is the matrix whose ith row is z'(i) and beta = (beta(1), ..., beta r)' is a vector of parameters. We focus...
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作者：CHAN, KS; GEYER, CJ
作者单位：University of Minnesota System; University of Minnesota Twin Cities
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作者：HALL, P; MAMMEN, E
作者单位：Ruprecht Karls University Heidelberg
摘要：Recent work of several authors has focussed on first-order properties (e.g, consistency) of general bootstrap algorithms, where the numbers of times that data values are resampled form an exchangeable sequence. In the present paper we develop second-order properties of such algorithms, in a very general setting. Performance is discussed in the context of distribution estimation, and formulae for higher-order moments and cumulants are developed. Arguing thus, necessary and sufficient conditions...
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作者：VANDERVAART, A
摘要：Suppose one observes independent samples of size n from both the mixture density integral p(x\z)d eta(z) and from the distribution eta. The kernel p(x\z) is known. We show asymptotic normality and efficiency of the maximum likelihood estimator for eta.
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作者：POLITIS, DN; ROMANO, JP
作者单位：Stanford University
摘要：In this article, the construction of confidence regions by approximating the sampling distribution of some statistic is studied. The true sampling distribution is estimated by an appropriate normalization of the values of the statistic computed over subsamples of the data. In the i.i.d. context, the method has been studied by Wu in regular situations where the statistic is asymptotically normal. The goal of the present work is to prove the method yields asymptotically valid confidence regions ...
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作者：RYDEN, T
摘要：Hidden Markov models are today widespread for modeling of various phenomena. It has recently been shown by Leroux that the maximum-likelihood estimate (MLE) of the parameters of a such a model is consistent, and local asymptotic normality has been proved by Bickel and Ritov. In this paper we propose a new class of estimates which are consistent, asymptotically normal and almost as good as the MLE.
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作者：DONNELL, DJ; BUJA, A; STUETZLE, W
作者单位：Telcordia Technologies
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作者：LAI, TL
摘要：Stochastic regression models of the form y(i) = f(i)(theta) + epsilon(i), where the random disturbances epsilon(i) form a martingale difference sequence with respect to an increasing sequence of sigma-fields {g(i)} and f(i) is a random g(i-1)-measurable function of an unknown parameter theta, cover a broad range of nonlinear (and linear) time series and stochastic process models. Herein strong consistency and asymptotic normality of the least squares estimate of theta in these stochastic regre...
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作者：TIERNEY, L
