搜索结果: 1-15 共查到“理论统计学 deconvolution”相关记录16条 . 查询时间(0.125 秒)
Noisy Laplace deconvolution with error in the operator
Laplace convolution blind deconvolution nonparametric adaptive estima-tion linear inverse problems error in the operator
2013/4/28
We adress the problem of Laplace deconvolution with random noise in a regression framework. The time set is not considered to be fixed, but grows with the number of observation points. Moreover, the c...
Revisiting Bayesian Blind Deconvolution
Blind deconvolution blind image deblurring variational Bayes sparse priors sparse estimation
2013/6/14
Blind deconvolution involves the estimation of a sharp signal or image given only a blurry observation. Because this problem is fundamentally ill-posed, strong priors on both the sharp image and blur ...
Multichannel Deconvolution with Long-Range Dependence: A Minimax Study
adaptivity Besov spaces block thresholding deconvolu-tion Fourier analysis functional data long-range dependence,Meyer wavelets mini-max estimators multichannel deconvolution partial differential equations stationary sequences wavelet analysis
2013/6/13
We consider the problem of estimating the unknown response function in the multichannel deconvolution model with long-range dependent Gaussian errors. We do not limit our consideration to a specific t...
Adaptive quantile estimation in deconvolution with unknown error distribution
Deconvolution Quantile and distribution function Adaptive es-timation Minimax convergence rates Random Fourier multiplier
2013/4/27
We study the problem of quantile estimation in deconvolution with ordinary smooth error distributions. In particular, we focus on the more realistic setup of unknown error distributions. We develop a ...
Laplace deconvolution with noisy observations
adaptivity kernel estimation minimax rates Volterra equation
2011/7/19
In the present paper we consider Laplace deconvolution on the basis of discrete noisy data observed on the interval which length may increase with a sample size. Although this problem arises in a vari...
Kernel methods and minimum contrast estimators for empirical deconvolution
bandwidth inverse problems kernel estimators local linearmethods local polynomial methods minimum contrast methods
2010/3/11
We survey classical kernel methods for providing nonparametric solutions
to problems involving measurement error. In particular we outline
kernel-basedmethodology in this setting, and discuss its ba...
Deconvolution in High-Energy Astrophysics: Science, Instrumentation, and Methods
Background Contamination Censoring Chandra X-ray Observatory EM-type Algorithms Frequency Evaluations Markov chain Monte Carlo Measurement Errors
2009/9/21
In recent years, there has been an avalanche of new data in observa-
tional high-energy astrophysics. Recently launched or soon-to-be launched space-
based telescopes that are designed to detect and...
Deconvolution with unknown error distribution
Deconvolution Fourier transform kernel estimation spectralcut off Sobolev space source condition optimal rate of convergence
2010/4/29
We assume that an additional sample x1, . . . , xm from fx is observed.
Estimators of fX and its derivatives are constructed by using nonparametric
estimators of fY and fx and by applying a spectral...
On the usefulness of Meyer wavelets for deconvolution and density estimation
Density estimation Deconvolution Inverse problem Wavelet thresholding Random thresholds Oracle inequalities
2010/3/18
The aim of this paper is to show the usefulness of Meyer wavelets for the classical problem of
density estimation and for density deconvolution fromnoisy observations. By using suchwavelets, the comp...
Functional deconvolution in a periodic setting：Uniform case
Adaptivity Besov spaces block thresholding deconvolution Fourier analysis functional data Meyer wavelets
2010/4/27
We extend deconvolution in a periodic setting to deal with functional
data. The resulting functional deconvolution model can be
viewed as a generalization of a multitude of inverse problems in mathe...
Deconvolution density estimation with heteroscedastic errors using SIMEX
Density estimation deconvolution measurementerrors SIMEX heteroscedasticity
2010/3/18
In many real applications, the distribution of measurement error
could vary with each subject or even with each observation so the errors
are heteroscedastic. In this paper, we propose a fast algori...
Testing distribution in deconvolution problems
contaminated data Laguerre polynomials Meixnerpolynomials Legendre polynomials
2010/3/17
In this paper we consider a random variable Y contamined by
an independent additive noise Z.We assume that Z has known distribution.
Our purpose is to test the distribution of the unobserved random ...
Unsupervised bayesian convex deconvolution based on a field with an explicit partition function
Deconvolution Bayesian statistics regularization convex potentials partition function hyperparametersestimation
2010/3/17
This paper proposes a non-Gaussian Markov field with a special feature: an explicit partition function.To the best of our knowledge, this is an original contribution. Moreover, the explicit expression...
Data-driven efficient score tests for deconvolution problems
Hypothesis testing statistical inverse problems deconvolution efficient score test model selection data-driven test
2010/4/30
We consider testing statistical hypotheses about densities of
signals in deconvolution models. A new approach to this problem is proposed.
We constructed score tests for the deconvolution with the k...
Undercomplete Blind Subspace Deconvolution via Linear Prediction
Undercomplete Blind Subspace Deconvolution Linear Prediction
2010/4/29
Undercomplete Blind Subspace Deconvolution via Linear Prediction。