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We examine adaptive finite element methods (AFEM) with any polynomial degree satisfying rather general assumptions on the a posteriori error estimators. We show that several non-residual estimat...
Motivated by estimation and testing with doubly censored data, we study (robust) Lestimators and M-estimators based on such data. These estimators are given through functionals of the self-consistent ...
We study the detailed structure (in a large sample) of the self-consistent estimators of the survival functions with doubly censored data. We also introduce the kernel-type density estimators based on...
This paper explores the properties of pre-test strategies in estimating a linear Cliff–Ord-type spatial model when the researcher is unsure about the nature of the spatial dependence. More speciʂ...
For1 dimension reduction in the l1 norm, the method of Cauchy random projections multiplies the original data matrix A Rn×D with a random matrix R RD×k (k  D) whose entries are i.i.d. samples of ...
Donoho and Johnstone (1998) studied a setting where data were obtained in the continuum white noise model and showed that scalar nonlinearities applied to wavelet coefficients gave estimators w...
ON INCONSISTENT M-ESTIMATORS.
In an increasing number of applications, it is of interest to recover an approximately low-rank data matrix from noisy observations. This paper develops an unbiased risk estimate—holding in a Gaussian...
The entropy rate of a hidden Markov process (HMP) is important in theory and practical applications, but it is hard to get an analytical expression or obtain a numerical estimator. In this paper, a ne...
Context. Over the past few years several studies have provided estimates of the SFR (star–formation rate) or the total infrared luminosity from just one infrared band. However these relations are gene...
For the zone of moderate deviation probabilities the local asymptotic minimax lower bound of asymptotic efficiency of estimators is established. The estimation parameter is multidimensional. The lower...
We introduce a data-based approach to estimating key quantities which arise in the study of nonlinear control systems and random nonlinear dynamical systems. Our approach hinges on the observation tha...
Abstract: In this paper, a lower bound is determined in the minimax sense for change point estimators of the first derivative of a regression function in the fractional white noise model. Similar mini...
Abstract: We introduce kernel estimators for the semicircle law. In this first part of our general theory on the estimators, we prove the consistency and conduct simulation study to show the performan...

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