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作者：Einmahl, U; Mason, DM
作者单位：Vrije Universiteit Brussel; University of Delaware
摘要：We introduce a general method to prove uniform in bandwidth consistency of kernel-type function estimators. Examples include the kernel density estimator, the Nadaraya-Watson regression estimator and the conditional empirical process. Our results may be useful to establish uniform consistency of data-driven bandwidth kernel-type function estimators.
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作者：Guerre, E; Lavergne, P
作者单位：Sorbonne Universite; Universite PSL; Ecole des Hautes Etudes en Sciences Sociales (EHESS); Universite de Toulouse; Universite Toulouse 1 Capitole; Centre National de la Recherche Scientifique (CNRS)
摘要：We propose new data-driven smooth tests for a parametric regression function. The smoothing parameter is selected through a new criterion that favors a large smoothing parameter under the null hypothesis. The resulting test is adaptive rate-optimal and consistent against Pitman local alternatives approaching the parametric model at a rate arbitrarily close to I/root n. Asymptotic critical values come from the standard normal distribution and the bootstrap can be used in small samples. A genera...
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作者：Tiur, T
作者单位：Copenhagen Business School
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作者：Shah, KR; Bose, M; Raghavarao, D
作者单位：University of Waterloo; Indian Statistical Institute; Indian Statistical Institute Kolkata; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
摘要：We show that the balanced crossover designs given by Patterson [Biometrika 39 (1952) 32-48] are (a) universally optimal (UO) for the joint estimation of direct and residual effects when the competing class is the class of connected binary designs and (b) UO for the estimation of direct (residual) effects when the competing class of designs is the class of connected designs (which includes the connected binary designs) in which no treatment is given to the same subject in consecutive periods. I...
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作者：Bartlett, PL; Bousquet, O; Mendelson, S
作者单位：University of California System; University of California Berkeley; University of California System; University of California Berkeley; Max Planck Society; Australian National University
摘要：We propose new bounds on the error of learning algorithms in terms of a data-dependent notion of complexity. The estimates we establish give optimal rates and are based on a local and empirical version of Rademacher averages, in the sense that the Rademacher averages are computed from the data, on a subset of functions with small empirical error. We present some applications to classification and prediction with convex function classes, and with kernel classes in particular.
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作者：Lehmann, EL; Romano, JP
作者单位：University of California System; University of California Berkeley; Stanford University
摘要：H-1,..., H-s. The usual approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, particularly if s is large, one might be willing to tolerate more than one false rejection provided the number of such cases is controlled, thereby increasing the ability of the procedure to detect false null hypotheses. This suggests replacing control of the FWER by con...
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作者：Reboul, L
作者单位：Universite de Poitiers; Universite Gustave-Eiffel
摘要：This paper deals with a nonparametric shape respecting estimation method for U-shaped or unimodal functions. A general upper bound for the nonasymptotic L-1-risk of the estimator is given. The method is applied to the shape respecting estimation of several classical functions, among them typical intensity functions encountered in the reliability field. In each case, we derive from our upper bound the spatially adaptive property of our estimator with respect to the L-1-metric: it approximately ...
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作者：Paulo, R
摘要：Motivated by the statistical evaluation of complex computer models, we deal with the issue of objective prior specification for the parameters of Gaussian processes. In particular, we derive the Jeffreys-rule, independence Jeffreys and reference priors for this situation, and prove that the resulting posterior distributions are proper under a quite general set of conditions. A proper flat prior strategy, based on maximum likelihood estimates, is also considered, and all priors are then compare...
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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：We determine optimal designs for some regression models which are frequently used for describing three-dimensional shapes. These models are based on a Fourier expansion of a function defined on the unit sphere in terms of spherical harmonic basis functions. In particular, it is demonstrated that the uniform distribution on the sphere is optimal with respect to all Phi(p) criteria proposed by Kiefer in 1974 and also optimal with respect to a criterion which maximizes a p mean of the r smallest ...
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作者：Jiang, JM
作者单位：University of California System; University of California Davis
摘要：In mixed linear models with nonnormal data, the Gaussian Fisher information matrix is called a quasi-information matrix (QUIM). The QUIM plays an important role in evaluating the asymptotic covariance matrix of the estimators of the model parameters, including the variance components. Traditionally, there are two ways to estimate the information matrix: the estimated information matrix and the observed one. Because the analytic form of the QUIM involves parameters other than the variance compo...
