搜索结果: 1-6 共查到“统计学其他学科 deconvolution”相关记录6条 . 查询时间(0.053 秒)
Wavelet Deconvolution in a Periodic Setting with Long-Range Dependent Errors
Besov Spaces Deconvolution fractional Brownian motion Long-Range Dependence Maxiset theory Wavelet Analysis
2012/9/17
In this paper, a hard thresholding wavelet estimator is constructed for a deconvolution model in a periodic setting that has long-range dependent noise. The estimation paradigm is based on a maxiset m...
A uniform central limit theorem and efficiency for deconvolution estimators
Deconvolution Donsker theorem Efficiency Distribution function Smoothed empirical processes Fourier multiplier
2012/9/17
We estimate linear functionals in the classical deconvolution problem by kernel esti-mators. We obtain a uniform central limit theorem with √n–rate on the assumption that the smoothness of the functio...
Laplace deconvolution and its application to Dynamic Contrast Enhanced imaging
Laplace deconvolution complexity penalty Dynamic Contrast Enhanced imaging
2012/9/19
In the present paper we consider the problem of Laplace deconvolution with noisy discrete observations. The study is motivated by Dynamic Contrast Enhanced imaging using a bolus of contrast agent, a p...
Multiscale Methods for Shape Constraints in Deconvolution
Brownian motion convexity di erential inequalities ill-posed problems
2011/7/19
We derive multiscale statistics for deconvolution in order to detect qualitative features of the unknown density. An important example covered within this framework is to test for local monotonicity o...
Nonparametric deconvolution problem for dependent sequences
long range dependence linear processes error-in-variables models deconvolution
2009/9/16
We consider the nonparametric estimation of the density function of weakly and strongly dependent processes with noisy observations. We show that in the ordinary smooth case the optimal bandwidth choi...
Deconvolution for an atomic distribution
Asymptotic normality atomic distribution deconvolution kernel density estimator
2009/9/16
Let $X_1,ldots, X_n$ be i.i.d. observations, where $X_i=Y_i+sigma Z_i $ and $Y_i$ and $Z_i$ are independent. Assume that unobservable $Y$'s are distributed as a random variable $UV$, where $U$ and $V$...