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昆明理工大学理学院概率论与数理统计课件Chapter 7 Estimation Problems--The particular properties of estimators
昆明理工大学理学院 概率论与数理统计 课件 Chapter 7 Estimation Problems The particular properties of estimators
2017/4/17
昆明理工大学理学院概率论与数理统计课件Chapter 7 Estimation Problems--The particular properties of estimators.
Quasi-Optimal Cardinality of AFEM Driven by Nonresidual Estimators
Error reduction convergence optimal cardinality adaptive algorithm
2015/12/11
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...
L-estimators and m-estimators for doubly censored data
Asymptotic normality asymptotic variance Fredholm integral equation Hadamard differentiability self-consistent estimator strong consistency
2015/12/11
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 ...
On self-consistent estimators and kernel density estimators with doubly censored data
Asymptotic normality Failure rate function Right censored data: Survival distribution Uniform strong consistency
2015/12/11
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...
Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections
dimension reduction l1 norm Johnson-Lindenstrauss (JL) lemma Cauchy random projections
2015/8/21
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 ...
ASYMPTOTIC MINIMAXITY OF WAVELET ESTIMATORS WITH SAMPLED DATA
Besov spaces bounded operators between Besov spaces
2015/8/20
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.
Unbiased Risk Estimates for Singular Value Thresholding and Spectral Estimators
Singular value thresholding Stein’s unbiased risk estimate (SURE) differentiability of eigenvalues and eigenvectors magnetic resonance cardiac imaging
2015/6/17
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 Sharp Lower Bound of Asymptotic Efficiency of Estimators in the Zone of Moderate Deviation Probabilities
The Sharp Lower Bound Asymptotic Efficiency of Estimators the Zone of Moderate Deviation Probabilities Statistics Theory
2012/6/27
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...
Empirical Estimators for Stochastically Forced Nonlinear Systems: Observability, Controllability and the Invariant Measure
Empirical Estimators Stochastically Forced Nonlinear Systems Invariant Measure Optimization and Control
2012/4/18
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...
Minimax lower bound for kink location estimators in a nonparametric regression model with long-range dependence
nonparametric regression long-range dependence kink minimax
2011/9/22
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...
New estimators of spectral distributions of Wigner matrices
Wigner matrices Stieltjes transform nonparametric estimate domain of attraction of normal law
2011/9/6
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...
Functional kernel estimators of large conditional quantiles
Conditional quantiles heavy-tailed distributions functional kernel estimator extreme-value theory
2011/9/2
Abstract: We address the estimation of conditional quantiles when the covariate is functional and when the order of the quantiles converges to one as the sample size increases. In a first time, we inv...
Bias correction for estimators of the extremal index
absolute regularity clustering of extremes extremal index empirical cluster process bias reduction
2011/9/29
Abstract: We investigate the joint asymptotic behavior of so-called blocks estimator of the extremal index, that determines the mean length of clusters of extremes, based on the exceedances over diffe...
Non-Parametric Maximum Likelihood Density Estimation and Simulation-Based Minimum Distance Estimators
Non-Parametric Maximum Likelihood Density Estimation Simulation-Based Minimum Distance Estimators
2011/2/22
Indirect inference estimators (i.e., simulation-based minimum distance estimators) in a
parametric model that are based on auxiliary non-parametric maximum likelihood density
estimators are shown to...