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作者：Kosorok, MR; Lee, BL; Fine, JP
作者单位：University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; National University of Singapore
摘要：We consider a class of semiparametric regression models which are one-parameter extensions of the Cox [J. Roy. Statist. Soc. Ser B 34 (1972) 187-220] model for right-censored univariate failure times. These models assume that the hazard given the covariates and a random frailty unique to each individual has the proportional hazards form multiplied by the frailty. The frailty is assumed to have mean 1 within a known one-parameter family of distributions. Inference is based on a nonparametric li...
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作者：Zeng, DL
作者单位：University of North Carolina; University of North Carolina Chapel Hill
摘要：One goal in survival analysis of right-censored data is to estimate the marginal survival function in the presence of dependent censoring. When many auxiliary covariates are sufficient to explain the dependent censoring, estimation based on either a semiparametric model or a nonparametric model of the conditional survival function can be problematic due to the high dimensionality of the auxiliary information. In this paper, we use two working models to condense these high-dimensional covariate...
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作者：Efron, B; Hastie, T; Johnstone, I; Tibshirani, R
作者单位：Stanford University
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作者：Jiang, WX
作者单位：Northwestern University
摘要：Recent experiments and theoretical studies show that AdaBoost can overfit in the limit of large time. If running the algorithm forever is suboptimal, a natural question is how low can the prediction error be during the process of AdaBoost? We show under general regularity conditions that during the process of AdaBoost a consistent prediction is generated, which has the prediction error approximating the optimal Bayes error as the sample size increases. This result suggests that, while running ...
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作者：Dette, H; Melas, VB; Pepelyshev, A
作者单位：Ruhr University Bochum; Saint Petersburg State University
摘要：For a broad class of nonlinear regression models we investigate the local E- and c-optimal design problem. It is demonstrated that in many cases the optimal designs with respect to these optimality criteria are supported at the Chebyshev points, which are the local extrerna of the equi-oscillating best approximation of the function f(0) equivalent to 0 by a normalized linear combination of the regression functions in the corresponding linearized model. The class of models includes rational, lo...
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作者：Komaki, F
作者单位：University of Tokyo
摘要：Simultaneous predictive distributions for independent Poisson observables are investigated. A class of improper prior distributions for Poisson means is introduced. The Bayesian predictive distributions based on priors from the introduced class are shown to be admissible under the Kullback-Leibler loss. A Bayesian predictive distribution based on a prior in this class dominates the Bayesian predictive distribution based on the Jeffreys prior.
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作者：Luati, A
作者单位：University of Bologna
摘要：We deal with the maximization of classical Fisher information in a quantum system depending on an unknown parameter. This problem has been raised by physicists, who defined [Helstrom (1967) Phys. Lett. A 25 101-102] a quantum counterpart of classical Fisher information, which has been found to constitute an upper bound for classical information itself [Braunstein and Caves (1994) Phys. Rev. Lett. 72 3439-3443]. It has then become of relevant interest among statisticians, who investigated the r...
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作者：Hu, FF; Zhang, LX
作者单位：University of Virginia; Zhejiang University
摘要：A general doubly adaptive biased coin design is proposed for the allocation of subjects to K treatments in a clinical trial. This design follows the same spirit as Efron's biased coin design and applies to the cases where the desired allocation proportions are unknown, but estimated sequentially. Strong consistency, a law of the iterated logarithm and asymptotic normality of this design are obtained under some widely satisfied conditions. For two treatments, a new family of designs is proposed...
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作者：Berkes, I; Horváth, L
作者单位：Hungarian Academy of Sciences; HUN-REN; HUN-REN Alfred Renyi Institute of Mathematics; Utah System of Higher Education; University of Utah
摘要：We propose a class of estimators for the parameters of a GARCH(p, q) sequence. We show that our estimators are consistent and asymptotically normal under mild conditions. The quasi-maximum likelihood and the likelihood estimators are discussed in detail. We show that the maximum likelihood estimator is optimal. If the tail of the distribution of the innovations is polynomial, even a quasi-maximum likelihood estimator based on exponential density performs better than the standard normal density...
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作者：Zhang, T
作者单位：International Business Machines (IBM); IBM USA
摘要：The discussants contributed different views on several aspects of large margin classification methods and outlined some interesting future directions. I would like to thank them for the stimulating comments. In the following I will mainly focus on two issues. One is the conditional probability modeling aspect of large margin classification methods and the other is related to properties of greedy algorithms used in boosting procedures.
