搜索结果: 1-10 共查到“数理统计学 wavelet”相关记录10条 . 查询时间(0.015 秒)
Ideal Spatial Adaptation by Wavelet Shrinkage
Minimax estimation sub ject to doing well at a point Orthogonal Wavelet Bases of Compact Support
2015/8/20
With ideal spatial adaptation, an oracle furnishes information about how best to
adapt a spatially variable estimator, whether piecewise constant, piecewise polynomial,
variable knot spline, or vari...
Minimax Bayes, asymptotic minimax and sparse wavelet priors
Minimax Decision theory Minimax Bayes estimation
2015/8/20
Pinsker(1980) gave a precise asymptotic evaluation of the minimax mean squared
error of estimation of a signal in Gaussian noise when the signal is known a priori
to lie in a compact ellipsoid in Hi...
This paper explores a class of empirical Bayes methods for levedependent threshold selection in wavelet shrinkage. The prior considered
for each wavelet coefficient is a mixture of an atom of p...
Wavelet deconvolution in a periodic setting
Adaptive estimation Deconvolution Meyer wavelet
2015/8/20
Deconvolution problems are naturally represented in the Fourier domain, whereas
thresholding in wavelet bases is known to have broad adaptivity properties. We study a method
which combines both fast...
WAVELET SHRINKAGE FOR CORRELATED DATA AND INVERSE PROBLEMS: ADAPTIVITY RESULTS
Adaptation correlated data fractional brownian motion
2015/8/20
Johnstone and Silverman (1997) described a level-dependent thresholding
method for extracting signals from correlated noise. The thresholds were chosen
to minimize a data based unbiased risk criteri...
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...
Wavelets have motivated development of a host of new ideas in nonparametric
regression smoothing. Here we apply the tool of exact risk analysis, to understand the
small sample behavior of wavelet es...
We attempt to recover an unknown function from noisy, sampled data. Using
orthonormal bases of compactly supported wavelets we develop a nonlinear method
which works in the wavelet domain by simple ...
Wavelet thresholding estimation in a Poissonian interactions model with application to genomic data
Adaptive estimation interactions model oracle inequalities Poisson process thresholding rule U-statistics wavelets
2011/9/16
Abstract: This paper deals with the study of dependencies between two given events modeled by point processes. In particular, we focus on the context of DNA to detect favored or avoided distances betw...
Adaptive semiparametric wavelet estimator and goodness-of-fit test for long memory linear processes
Long range dependence linear processes wavelet estimator semiparametric estimator
2011/1/18
This paper is first devoted to study an adaptive wavelet based estimator of the long memory parameter for linear processes in a general semi-parametric frame. This is an extension of Bardet et al. (20...