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作者：Sun, JY; Loader, C; McCormick, WP
作者单位：University System of Ohio; Case Western Reserve University; AT&T; Alcatel-Lucent; Lucent Technologies; University System of Georgia; University of Georgia
摘要：Generalized linear models (GLM) include many useful models. This paper studies simultaneous confidence regions for the mean response function in these models. The coverage probabilities of these regions are related to tail probabilities of maxima of Gaussian random fields, asymptotically, and hence, the so-called tube formula is applicable without any modification. However, in the generalized linear models, the errors are often nonadditive and non-Gaussian and may be discrete. This poses a cha...
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作者：Buja, A
作者单位：AT&T
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作者：Friedman, J; Hastie, T; Tibshirani, R
作者单位：Stanford University
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作者：Liang, TC
作者单位：Wayne State University
摘要：We exhibit an empirical Bayes test delta(n)(*) for the normal mean testing problem using a linear error loss. Under the condition that the critical point of a Bayes test is within some known compact interval, delta(n)(*) is shown to be asymptotically optimal and its associated regret Bayes risk converges to zero at a rate O(n(-1)(ln n)(1.5)), where n is the number of past experiences available when the current component decision problem is considered. Under the same condition this rate is fast...
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作者：Arcones, MA; Samaniego, FJ
作者单位：State University of New York (SUNY) System; Binghamton University, SUNY; University of California System; University of California Davis
摘要：We identify the asymptotic behavior of the estimators proposed by Rojo and Samaniego and Mukejee of a distribution F assumed to be uniformly stochastically smaller than a known baseline distribution G. We show that these estimators are root n-convergent to a limit distribution with mean squared error smaller than or equal to the mean squared error of the empirical survival function. By examining the mean squared error of the limit distribution, we are able to identify the optimal estimator wit...
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作者：Fuh, CD; Hu, IC
作者单位：Academia Sinica - Taiwan; Hong Kong University of Science & Technology
摘要：Motivated by an application in computerized adaptive tests, we consider the following sequential design problem. There are J jobs to be processed according to a predetermined order. A single machine is available to process these J jobs. Each job under processing evolves stochastically as a Markov chain and earns rewards as it is processed, not otherwise. The Markov chain has transition probabilities parameterized by an unknown parameter theta. The objective is to determine how long each job sh...
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作者：Dmitrienko, A; Govindarajulu, Z
作者单位：Eli Lilly; Lilly Research Laboratories; University of Kentucky
摘要：The goal of this paper is ti,develop a general framework for constructing sequential fixed size confidence regions based on maximum likelihood estimates. Asymptotic properties of the sequential procedure for setting up the confidence regions are analyzed under very broad assumptions on the underlying parametric model. It is shown that the proposed sequential procedure is asymptotically optimal in the sense that it approximates the optimal fixed-sample size procedure. It is further shown that t...
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作者：Mikosch, T; Starica, C
作者单位：University of Groningen; Chalmers University of Technology
摘要：The asymptotic theory for the sample autocorrelations and extremes of a GARCH(I, 1) process is provided. Special attention is given to the case when the sum of the ARCH and GARCH parameters is close to 1, that is, when one is close to an infinite Variance marginal distribution. This situation has been observed for various financial log-return series and led to the introduction of the IGARCH model. In such a situation, the sample autocorrelations are unreliable estimators of their deterministic...
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作者：Breiman, L
作者单位：University of California System; University of California Berkeley
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作者：Cavalier, L
作者单位：Aix-Marseille Universite
摘要：The aim of tomography is to reconstruct a multidimensional function From observations of its integrals over hyperplanes. We consider the model that corresponds to the case of positron emission tomography. We have n i.i.d. observations from a probability density proportional to Rf, where Rf stands for the Radon transform of the density f. We assume that f is an N-dimensional density such that its Fourier transform is exponentially decreasing. We find an estimator of f which is asymptotically ef...
