Given data from a sample of noisy curves in a nonlinear parametric regression model we consider nonparametric estimation of the model function and the parameters under certain structural assumptions. An algorithm for a consistent estimator is proposed and examples given.

Brief summaries and user instruction are presented for the programs TRAMO ("Time Series regression with ARIMA Noise, Missing Observations and Outlers") and SEATS ("Signal Extraction in ARIMA Time Series").

When stochastic errors are added to data from a distribution with a sharp boundary, such as a changepoint or a frontier, nonparametric estimation of the boundary can be interpreted as a problem of deconvolution. We argue that, rather than attempting to estimate the distribution of the...

This paper proposes to use a semi parametric regression method, named Sliced Inverse Regression (SIR hereafter), to analyse ambulatory blood pressure monitoring data.

This paper presents a new simulated maximum-likelihood method that rests on estimating the likelihood nonparametrically on a simulated sample. We prove that this method, which can be used on very general models, is consistent and asymptotically efficient.

We propose a minimax statistical framework adapted to nonparametric estimation in deterministic dynamical system, which highlights the importance of the recurrence property of the observed process. Estimators are evaluated on the basis of a weighted uniform norm. The weight function rn depends...

In 1990, Hjort introduced nonparametric Bayes estimators of the cumulative distribution function and the cumulative hazard rate, based on type I censored data. Our aim in this paper is to study their large sample behaviour. Firstly, we develop a martingale structure for each estimator. Then, we...

Empirical demand systems that do not impose unreasonable restrictions on preferences are typically nonlinear. For empirical purposes, exact estimation of nonlinear equation systems for large data sets with more than a small number of equations has typically been limited by nonlinearities in the...