International audienceIn this paper for the first time the nonparametric autoregression estimation problem for the quadratic risks is considered. To this end we develop a new adaptive sequential model selection method based on the efficient sequential kernel estimators proposed by Arkoun and Pergamenshchikov (2016). Moreover, we develop a new analytical tool for general regression models to obtain the non asymptotic sharp oracle inequalities for both usual quadratic and robust quadratic risks. Then, we show that the constructed sequential model selection procedure is optimal in the sense of oracle inequalities
We propose a general class of risk measures which can be used for data-based evaluation of parametri...
International audienceThe paper deals with asymptotic properties of the adaptive procedure proposed ...
We show that analyzing model selection in ARMA time series models as a quadratic discrimination prob...
International audienceIn this paper for the first time the nonparametric autoregression estimation p...
In this paper for the first time the adaptive efficient estimation problem for nonparametric autoreg...
We constuct a sequential adaptive procedure for estimating the autoregressive function at a given po...
International audienceWe construct a robust truncated sequential estimator for the point- wise estim...
We construct efficient robust truncated sequential estimators for the pointwise estimation problem i...
In this paper we consider high dimension models based on dependent observations defined through auto...
34 pagesAn adaptive nonparametric estimation procedure is constructed for the estimation problem of ...
The paper deals with asymptotic properties of the adaptive procedure proposed in the author paper, 2...
In this paper, we consider the robust adaptive non parametric estimation problem for the periodic fu...
In this paper we prove the asymptotic efficiency of the model selection procedure proposed by the au...
In this paper, we develop the James–Stein improved method for the estimation problem of a nonparamet...
International audienceThis paper deals with the estimation of a autoregression function at a given p...
We propose a general class of risk measures which can be used for data-based evaluation of parametri...
International audienceThe paper deals with asymptotic properties of the adaptive procedure proposed ...
We show that analyzing model selection in ARMA time series models as a quadratic discrimination prob...
International audienceIn this paper for the first time the nonparametric autoregression estimation p...
In this paper for the first time the adaptive efficient estimation problem for nonparametric autoreg...
We constuct a sequential adaptive procedure for estimating the autoregressive function at a given po...
International audienceWe construct a robust truncated sequential estimator for the point- wise estim...
We construct efficient robust truncated sequential estimators for the pointwise estimation problem i...
In this paper we consider high dimension models based on dependent observations defined through auto...
34 pagesAn adaptive nonparametric estimation procedure is constructed for the estimation problem of ...
The paper deals with asymptotic properties of the adaptive procedure proposed in the author paper, 2...
In this paper, we consider the robust adaptive non parametric estimation problem for the periodic fu...
In this paper we prove the asymptotic efficiency of the model selection procedure proposed by the au...
In this paper, we develop the James–Stein improved method for the estimation problem of a nonparamet...
International audienceThis paper deals with the estimation of a autoregression function at a given p...
We propose a general class of risk measures which can be used for data-based evaluation of parametri...
International audienceThe paper deals with asymptotic properties of the adaptive procedure proposed ...
We show that analyzing model selection in ARMA time series models as a quadratic discrimination prob...
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