Adaptive wavelet estimation of a function in an indirect regression model

Adaptive wavelet estimation of a function in an indirect regression model

We consider a nonparametric regression model where m noiseperturbed functions f1, . . . , fm are randomly observed. For a fixed ν ∈ {1, . . . ,m}, we want to estimate fν from the observations. To reach this goal, we develop an adaptive wavelet estimator based on a hard thresholding rule. Adopting the minimax approach under the mean integrated squared error over Besov balls, we prove that it att...

On adaptive wavelet estimation of the regression function and its derivatives in an errors-in-variables model

We consider a regression model with errors-in-variables: (Y,X), where Y = f(Z) + ξ and X = Z + W . Our goal is to estimate the unknown regression function f and its derivatives under mild assumptions on ξ (only finite moments of order 2 are required). To reach this goal, we develop a new adaptive wavelet estimator based on a hard thresholding rule. Taking the minimax approach under the mean int...

A Visually Adaptive Bayesian Model In Wavelet Regression

cost benefits of rehabilitation after acute coronary syndrome in iran; using an epidemiological model

چکیده ندارد.

Wavelet Threshold Estimator of Semiparametric Regression Function with Correlated Errors

Wavelet analysis is one of the useful techniques in mathematics which is used much in statistics science recently. In this paper, in addition to introduce the wavelet transformation, the wavelet threshold estimation of semiparametric regression model with correlated errors with having Gaussian distribution is determined and the convergence ratio of estimator computed. To evaluate the wavelet th...