-
作者：Moulines, E; Soulier, P
作者单位：IMT - Institut Mines-Telecom; Institut Polytechnique de Paris; Telecom Paris; Universite Paris Saclay
摘要：This paper discusses the properties of an estimator of the memory parameter of a stationary long-memory time-series originally proposed by Robinson. As opposed to narrow-band estimators of the memory parameter (such as the Geweke and Porter-Hudak or the Gaussian semiparametric estimators) which use only the periodogram ordinates belonging to an interval which degenerates to zero as the sample size n increases, this estimator builds a model of the spectral density of the process over all the fr...
-
作者：Cabrera, J; Fernholz, LT
作者单位：Rutgers University System; Rutgers University New Brunswick; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
摘要：Given a statistical functional T and a parametric family of distributions, a bias reduced functional (T) over tilde is defined by setting the expected value of the statistic equal to the observed value. Under certain regularity conditions this new statistic, called the target estimator, will have smaller bias and mean square error than the original estimator. The theoretical aspects are analyzed by using higher order von Mises expansions. Several examples are given, including M-estimates of lo...
-
作者：Cai, TT
作者单位：Purdue University System; Purdue University
摘要：We study wavelet function estimation via the approach of block thresholding and ideal adaptation with oracle. Oracle inequalities are derived and serve as guides for the selection of smoothing parameters. Based on an oracle inequality and motivated by the data compression and localization properties of wavelets, an adaptive wavelet estimator for nonparametric regression is proposed and the optimality of the procedure is investigated. We show that the estimator achieves simultaneously three obj...
-
作者：Wang, HY
作者单位：Academia Sinica - Taiwan
摘要：A widely held notion of classical conditional theory is that statistical inference in the presence of ancillary statistics should he independent of the distribution of those ancillary statistcs. In this paper, ancillary paradoxes which contradict this notion are presented for two scenarios involving confidence estimation. These results are related to Brown's ancillary paradox in point estimation. Moreover, the confidence coefficient, the usual constant coverage probability estimator, is shown ...
-
作者：Yang, YH; Barron, A
作者单位：Iowa State University; Yale University
摘要：We present some general results determining minimax bounds on statistical risk for density estimation based on certain information-theoretic considerations. These bounds depend only on metric entropy conditions and are used to identify the minimax rales of convergence.
-
作者：Gassiat, E; Gautherat, E
作者单位：Universite Paris Saclay; Universite de Reims Champagne-Ardenne
摘要：In a recent paper, we proposed a new estimation method for the blind deconvolution of a linear system with discrete random input, when the observations may be noise perturbed. We give here asymptotic properties of the estimators in the parametric situation. With nonnoisy observations, the speed of convergence is governed by the Ii-tail of the inverse filter. which may have an exponential decrease. With noisy observations, the estimator satisfies a limit theorem with known distribution, which a...
-
作者：Mizera, I; Müller, CH
作者单位：Comenius University Bratislava; University of Gottingen
摘要：The breakdown point behavior of M-estimators in linear models with fixed designs, arising from planned experiments or qualitative factors, is characterized. Particularly, this behavior at fixed designs is quite different from that at designs which can be corrupted by outliers, the situation prevailing in the literature. For fixed designs, the breakdown points of robust M-estimators (those with bounded derivative of the score function), depend on the design and the variation exponent (index) of...
-
作者：Jensen, JL; Petersen, NV
作者单位：Aarhus University
摘要：State space models is a very general class of time series models capable of modelling dependent observations in a natural and interpretable way. Inference in such models has been studied by Bickel, Ritov and Ryden, who consider hidden Markov models, which are special kinds of state space models, and prove that the maximum likelihood estimator is asymptotically normal under mild regularity conditions. In this paper we generalize the results of Bickel, Ritov and Ryden to state space models, wher...
-
作者：Dawid, AP; Sebastiani, P
作者单位：University of London; University College London; Open University - UK
摘要：We characterize those coherent design criteria which depend only on the dispersion matrix (assumed proper and nonsingular) of the state of nature, which may be a parameter-vector or a set of future observables, and describe the associated decision problems. Connections are established with the classical approach to optimal design theory for the normal linear model, based on concave functions of the information matrix. Implications of the theory for more general models are also considered.
-
作者：Hassairi, A
作者单位：Universite de Sfax; Faculty of Sciences Sfax
摘要：Let mu be a positive measure on R-d and let F(mu) = {P(theta, mu); theta is an element of Theta} be the natural exponential family generated by mu. The aim of this paper is to show that if mu is infinitely divisible then the generalized variance of mu, i.e., the determinant of the covariance operator of P(theta, mu), is the Laplace transform of some positive measure rho(mu) on R-d. We then investigate the effect of the transformation mu --> rho(mu) and its implications for the skewness vector ...
