Block-threshold-adapted Estimators via a Maxiset Approach

Maxiset in sup-norm for kernel estimators

In the Gaussian white noise model, we study the estimation of an unknown multidimensional function f in the uniform norm by using kernel methods. The performances of procedures are measured by using the maxiset point of view: we determine the set of functions which are well estimated (at a prescribed rate) by each procedure. So, in this paper, we determine the maxisets associated to kernel esti...

A maxiset approach of a Gaussian noise model

Wavelet threshold estimators for data

Wavelet threshold estimators for data with stationary correlated noise are constructed by applying a level-dependent soft threshold to the coeecients in the wavelet transform. A variety of threshold choices are proposed, including one based on an unbiased estimate of mean squared error. The practical performance of the method is demonstrated on examples, including data from a neurophysiological...

Maxiset for Density Estimation

The problem of density estimation on R is concerned. Adopting the maxiset point of view, the aim of this paper is threefold. Firstly, we prove that the maxiset of any elitist rule is contained in the intersection of a Besov space and a weak Besov space. Secondly, we provide an adaptive procedure for which the maxiset is the largest one among elitist rules (ideal maxiset). Thirdly, we point out ...

Estimation of genetic parameters of litter size in Moghani sheep using threshold model via Bayesian approach

This study was conducted to estimate the genetic parameters of litter size (LS) in Moghani sheep using threshold model via Bayesian approach. The data originated from the Jafar-Abad Station of Ardabil province, Iran, and included 9698 lactation records of 4977 ewes with lambings from 1995 until 2010. The pedigree file consisted of data on animals born from 1987 to 2010. The significance of fixe...