This article provides the distribution of the last exit for strongly consistent estimators. Namely, we consider a small neighborhood of the (almost sure) limit and state the asymptotic distribution of the last time the estimator is outside this neighborhood. Such problems have been considered in the literature by various authors; this article extends these results in a semi-parametric frame. An application to adaptive estimation is provided. Copyright © Taylor & Francis Group, LLC
AbstractWe consider stationary autoregressive processes of order p which have positive innovations. ...
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An asymptotic theory for estimation and inference in adaptive learning models with strong mixing reg...
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International audienceIn This work, the asymptotic estimation of a class F of functional parameters ...
It is shown that (under some regularity conditions) minimum distance estimators for a (possibly mult...
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This is the authors’ final, accepted and refereed manuscript to the article. The final publication i...
We consider the consistency and weak convergence of $S$-estimators in the linear regression model. S...
We establish the asymptotic theory for the estimation of adaptive varying coefficient linear models....
We survey the asymptotic properties of regression Lp estimators under general classes of error distr...
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summary:This work deals with Random Coefficient Autoregressive models where the error process is a m...
AbstractWe consider stationary autoregressive processes of order p which have positive innovations. ...
This paper extends the asymptotic theory of GMM inference to allow sample counterparts of the estima...
An asymptotic theory for estimation and inference in adaptive learning models with strong mixing reg...
This paper considers a partially linear model of the form y = x beta + g(t) + e, where beta is an un...
International audienceIn This work, the asymptotic estimation of a class F of functional parameters ...
It is shown that (under some regularity conditions) minimum distance estimators for a (possibly mult...
Abstract: The main goal of this paper is to develop, under a semi-parametric context, asymptotically...
This is the authors’ final, accepted and refereed manuscript to the article. The final publication i...
We consider the consistency and weak convergence of $S$-estimators in the linear regression model. S...
We establish the asymptotic theory for the estimation of adaptive varying coefficient linear models....
We survey the asymptotic properties of regression Lp estimators under general classes of error distr...
This paper considers the problem of estimating probabilities of the form ℙ(Y ≤ w), for a given value...
We establish the asymptotic theory for the estimation of adaptive varying-coefficient linear models....
We consider an econometric model based on a set of moment conditions which are indexed by both a fini...
summary:This work deals with Random Coefficient Autoregressive models where the error process is a m...
AbstractWe consider stationary autoregressive processes of order p which have positive innovations. ...
This paper extends the asymptotic theory of GMM inference to allow sample counterparts of the estima...
An asymptotic theory for estimation and inference in adaptive learning models with strong mixing reg...