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作者：Hoffmann, M; Lepski, O
作者单位：Universite Paris Cite; Aix-Marseille Universite; Centre National de la Recherche Scientifique (CNRS)
摘要：We are grateful to all the participants for their stimulating comments and insightful questions. Reading the notes of the contributers, we progressively came to a better understanding of the imperfections of our approach. It also has given an orientation for further efforts: trying to answer their questions, we found several interesting problems for future work. We also believe and hope that this discussion will be relevant for potential readers since it somehow represents the state of modern ...
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作者：Nze, PA; Bühlmann, P; Doukhan, P
作者单位：Universite de Lille; Swiss Federal Institutes of Technology Domain; ETH Zurich; CY Cergy Paris Universite
摘要：We consider a new concept of weak dependence, introduced by Doukhan and Louhichi [Stochastic Process. Appl. 84 (1999) 313-342], which is more general than the classical frameworks of mixing or associated sequences. The new notion is broad enough to include many interesting examples such as very general Bernoulli shifts, Markovian models or time series bootstrap processes with discrete innovations. Under such a weak dependence assumption, we investigate nonparametric regression which represents...
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作者：Yang, YH; Zhu, D
作者单位：Iowa State University; Iowa State University
摘要：We study a multi-armed bandit problem in a setting where covariates are available. We take a nonparametric approach to estimate the functional relationship between the response (reward) and the covariates. The estimated relationships and appropriate randomization are used to select a good arm to play for a greater expected reward. Randomization helps balance the tendency to trust the currently most promising arm with further exploration of other arms, It is shown that, with some familiar nonpa...
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作者：Mizera, I
作者单位：University of Alberta; Comenius University Bratislava
摘要：For a general definition of depth in data analysis a differential-like calculus is constructed in which the location case (the framework of Tukey's median) plays a fundamental role similar to that of linear functions in the mathematical analysis. As an application, a lower bound for maximal regression depth is proved in the general multidimensional case-as conjectured by Rousseeuw and Hubert and others. This lower bound is demonstrated to have an impact on the breakdown point of the maximum de...
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作者：Fraser, DAS; Reid, N
作者单位：University of Toronto
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作者：Park, BU; Kim, WC; Jones, MC
作者单位：Seoul National University (SNU); Open University - UK
摘要：This paper considers a class of local likelihood methods introduced by Eguchi and Copas. Unified asymptotic results are presented in the usual smoothing context of the bandwidth, h, tending to zero as the sample size tends to infinity. We present our results pointwise in the univariate case, but then go on to extend them to global properties and to indicate how to cope with the multivariate case. Specific members of the class due to Copas, and Hjort and Jones are seen to be members of a subset...
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作者：Li, H
作者单位：University of Rochester
摘要：A particular linear group symmetry model, called the dyadic symmetry model, is studied in some detail. Statistical procedures analogous to (multivariate) analysis of variance are introduced. This model may be suitable for various kinds of data collected on pairs of sampling units. Examples include (complete) diallel cross experiments in genetics and social relations analysis in psychology, for which ad hoc methods of analysis have been developed independently in those disciplines. Our approach...
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作者：Wang, YZ
作者单位：University of Connecticut
摘要：This paper investigates the statistical relationship of the LARCH model and its diffusion limit. Regarding the two types of models as two statistical experiments formed by discrete observations from the models, we study their asymptotic equivalence in terms of Le Cam's deficiency distance. To our surprise, we are able to show that the LARCH model and its diffusion limit are asymptotically equivalent only under deterministic volatility. With stochastic volatility, due to the difference between ...
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作者：Gervini, D; Yohai, VJ
作者单位：University of Zurich; University of Buenos Aires; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
摘要：This paper introduces a new class of robust estimators for the linear regression model. They are weighted least squares estimators, with weights adaptively computed using the empirical distribution of the residuals of an initial robust estimator. It is shown that under certain general conditions the asymptotic breakdown points of the proposed estimators are not less than that of the initial estimator, and the finite sample breakdown point can be at most 1/n less. For the special case of the le...
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作者：Jiang, JM; Lahiri, P; Wan, SM
作者单位：University of California System; University of California Davis; University System of Maryland; University of Maryland College Park
摘要：The paper presents a unified jackknife theory for a fairly general class of mixed models which includes some of the widely used mixed linear models and generalized linear mixed models as special cases. The paper develops jackknife theory for the important, but so far neglected, prediction problem for the general mixed model. For estimation of fixed parameters, a jackknife method is considered for a general class of M-estimators which includes the maximum likelihood, residual maximum likelihood...
