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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...
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作者：Kulikov, VN; Lopuhaä, HP
作者单位：Delft University of Technology
摘要：We investigate the limit behavior of the L-k-distance between a decreasing density f and its nonparametric maximum likelihood estimator f, for k >= 1. Due to the inconsistency of (f) over cap (n) at zero, the case k = 2.5 turns out to be a kind of transition point. We extend asymptotic normality of the L-1-distance to the Lk-distance for I < k < 2.5, and obtain the analogous limiting result for a modification of the L-k-distance for k >= 2.5. Since the L-1-distance is the area between f and (f...
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作者：Robinson, PM
作者单位：University of London; London School Economics & Political Science
摘要：We consider a time series model involving a fractional stochastic component, whose integration order can lie in the stationary/invertible or nonstationary regions and be unknown, and an additive deterministic component consisting of a generalized polynomial. The model can thus incorporate competing descriptions of trending behavior. The stationary input to the stochastic component has parametric autocorrelation, but innovation with distribution of unknown form. The model is thus semiparametric...
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作者：Studer, M; Seifert, B; Gasser, T
作者单位：University of Zurich
摘要：Due to the curse of dimensionality, estimation in a multidimensional nonparametric regression model is in general not feasible. Hence, additional restrictions are introduced, and the additive model takes a prominent place. The restrictions imposed can lead to serious bias. Here, a new estimator is proposed which allows penalizing the nonadditive part of a regression function. This offers a smooth choice between the full and the additive model. As a byproduct, this penalty leads to a regulariza...
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作者：Gelman, A
作者单位：Columbia University
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作者：Chernozhukov, V
作者单位：Massachusetts Institute of Technology (MIT)
摘要：Quantile regression is an important tool for estimation of conditional quantiles of a response Y given a vector of covariates X. It can be used to measure the effect of covariates not only in the center of a distribution. but also in the upper and lower tails. This paper develops a theory of quantile regression in the tails. Specifically, it obtains the large sample properties of extremal (extreme order and intermediate order) quantile regression estimators for the linear quantile regression m...
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作者：Moulines, E; Priouret, P; Roueff, F
作者单位：IMT - Institut Mines-Telecom; Institut Polytechnique de Paris; Telecom Paris; Sorbonne Universite; Centre National de la Recherche Scientifique (CNRS); Sorbonne Universite
摘要：This paper focuses on recursive estimation of time varying autoregressive processes in a nonparametric setting. The stability of the model is revisited and uniform results are provided when the time-varying autoregressive parameters belong to appropriate smoothness classes. An adequate normalization for the correction term used in the recursive estimation procedure allows for very mild assumptions on the innovations distributions. The rate of convergence of the pointwise estimates is shown to ...
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作者：Hidalgo, J
作者单位：University of London; London School Economics & Political Science
摘要：We consider the estimation of the location of the pole and memory parameter, lambda(0) and alpha, respectively, of covariance stationary linear processes whose spectral density function f(lambda) satisfies f(lambda) similar to C vertical bar lambda - lambda(0)vertical bar(-alpha) in a neighborhood of lambda(0). We define a consistent estimator of lambda(0) and derive its limit distribution Z(lambda)0. As in related optimization problems, when the true parameter value can lie on the boundary of...
