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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...
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作者：Wu, WB
作者单位：University of Chicago
摘要：We establish the Bahadur representation of sample quantiles for linear and some widely used nonlinear processes. Local fluctuations of empirical processes are discussed. Applications to the trimmed and Winsorized means are given. Our results extend previous ones by establishing sharper bounds under milder conditions and thus provide new insight into the theory of empirical processes for dependent random variables.
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作者：Bhattacharya, R; Patrangenaru, V
作者单位：University of Arizona; Texas Tech University System; Texas Tech University
摘要：This article develops nonparametric inference procedures for estimation and testing problems for means on manifolds. A central limit theorem for Frechet sample means is derived leading to an asymptotic distribution theory of intrinsic sample means on Riemannian manifolds. Central limit theorems are also obtained for extrinsic sample means w.r.t. an arbitrary embedding of a differentiable manifold in a Euclidean space. Bootstrap methods particularly suitable for these problems are presented. Ap...
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作者：He, XM
作者单位：University of Illinois System; University of Illinois Urbana-Champaign
