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作者：Nordman, Daniel J.; Lahiri, Soumendra N.
作者单位：Iowa State University
摘要：This paper introduces a version of empirical likelihood based on the periodogram and spectral estimating equations. This formulation handles dependent data through a data transformation (i.e., a Fourier transform) and is developed in terms of the spectral distribution rather than a time domain probability distribution. The asymptotic properties of frequency domain empirical likelihood are studied for linear time processes exhibiting both short- and long-range dependence. The method results in ...
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作者：Hallin, Marc; Oja, Hannu; Paindaveine, Davy
作者单位：Universite Libre de Bruxelles; Universite Libre de Bruxelles; Tampere University
摘要：A class of R-estimators based on the concepts of multivariate signed ranks and the optimal rank-based tests developed in Hallin and Paindaveine [Ann. Statist. 34 (2006) 2707-2756] is proposed for the estimation of the shape matrix of an elliptical distribution. These R-estimators are root-n consistent under any radial density g, without any moment assumptions, and semiparametrically efficient at some prespecified density f. When based on normal scores, they are uniformly more efficient than th...
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作者：Shen, Xiaotong; Wang, Lifeng
作者单位：University of Minnesota System; University of Minnesota Twin Cities
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作者：Dahlhaus, Rainer; Polonik, Wolfgang
作者单位：Ruprecht Karls University Heidelberg; University of California System; University of California Davis
摘要：This paper deals with nonparametric maximum likelihood estimation for Gaussian locally stationary processes. Our nonparametric MLE is constructed by minimizing a frequency domain likelihood over a class of functions. The asymptotic behavior of the resulting estimator is studied. The results depend on the richness of the class of functions. Both sieve estimation and global estimation are considered. Our results apply, in particular, to estimation under shape constraints. As an example, autoregr...
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作者：Chen, Willa W.; Hurvich, Clifford M.
作者单位：Texas A&M University System; Texas A&M University College Station; New York University
摘要：We consider a common-components model for multivariate fractional cointegration, in which the s >= 1 components have different memory parameters. The cointegrating rank may exceed 1. We decompose the true cointegrating vectors into orthogonal fractional cointegrating subspaces such that vectors from distinct subspaces yield cointegrating errors with distinct memory parameters. We estimate each cointegrating subspace separately, using appropriate sets of eigenvectors of an averaged periodogram ...
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作者：Aslan, Mihaela
作者单位：US Department of Veterans Affairs; Veterans Health Administration (VHA); VA Connecticut Healthcare System; Yale University
摘要：Given a random sample from a distribution with density function that depends on an unknown parameter 0, we are interested in accurately estimating the true parametric density function at a future observation from the same distribution. The asymptotic risk of Bayes predictive density estimates with Kullback-Leibler loss function D(f(theta)parallel to(f) over cap) = integral (f) over cap (theta) log (f(theta)/(f) over cap) is used to examine various ways of choosing prior distributions; the prin...
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作者：Scricciolo, Catia
作者单位：Bocconi University
摘要：We study the rate of convergence of posterior distributions in density estimation problems for log-densities in periodic Sobolev classes characterized by a smoothness parameter p, The posterior expected density provides a nonparametric estimation procedure attaining the optimal minimax rate of convergence under Hellinger loss if the posterior distribution achieves the optimal rate over certain uniformity classes. A prior on the density class of interest is induced by a prior on the coefficient...
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作者：Chen, Aiyou; Bickel, Peter J.
作者单位：Alcatel-Lucent; Lucent Technologies; AT&T; University of California System; University of California Berkeley
摘要：Independent component analysis (ICA) has been widely used for blind source separation in many fields, such as brain imaging analysis, signal processing and telecommunication. Many statistical techniques based on M-estimates have been proposed for estimating the mixing matrix. Recently, several nonparametric methods have been developed, but in-depth analysis of asymptotic efficiency has not been available. We analyze ICA using semiparametric theories and propose a straightforward estimate based...
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作者：Boente, Graciela; He, Xuming; Zhou, Jianhui
作者单位：University of Buenos Aires; University of Buenos Aires; University of Illinois System; University of Illinois Urbana-Champaign; University of Virginia; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
摘要：In this paper, we introduce a family of robust estimates for the parametric and nonparametric components under a generalized partially linear model, where the data are modeled by y(i)vertical bar(x(i), t(i)) similar to F (center dot, mu(i)) with mu(i) = H(eta(t(i)) +X-i(t) beta), for some known distribution function F and link function H. It is shown that the estimates of fi are root-n consistent and asymptotically normal. Through a Monte Carlo study, the performance of these estimators is com...
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作者：Koltchinskii, Vladimir
作者单位：University System of Georgia; Georgia Institute of Technology
