Sequential adaptive design for jump regression estimation

Sequential Methods for Design-adaptive Estimation of Discontinuities in Regression Curves and Surfaces1 by Peter Hall

In fault-line estimation in spatial problems it is sometimes possible to choose design points sequentially, by working one’s way gradually through the “response plane,” rather than distributing design points across the plane prior to conducting statistical analysis. For example, when estimating a change line in the concentration of resources on or under the sea bed, individual measurements can ...

Adaptive sequential design for regression on multi-resolution bases

This work investigates the problem of construction of designs for estimation and discrimination between competing linear models. In our framework, the unknown signal is observed with the addition of a noise and only a few evaluations of the noisy signal are available. The model selection is performed in a multi-resolution setting. In this setting, the locations of discrete sequential D and A de...

Estimation of scour downstream of a ski-jump bucket using the multivariate adaptive regression splines

Pointwise adaptive estimation for quantile regression

A nonparametric procedure for quantile regression, or more generally nonparametric M-estimation, is proposed which is completely data-driven and adapts locally to the regularity of the regression function. This is achieved by considering in each point M-estimators over different local neighbourhoods and by a local model selection procedure based on sequential testing. Non-asymptotic risk bounds...

Adaptive Pointwise Estimation for Pure Jump Lévy Processes

This paper is concerned with adaptive kernel estimation of the Lévy density N(x) for bounded-variation pure-jump Lévy processes. The sample path is observed at n discrete instants in the ”high frequency” context (∆ = ∆(n) tends to zero while n∆ tends to infinity). We construct a collection of kernel estimators of the function g(x) = xN(x) and propose a method of local adaptive selection of the ...