Reference : Asymptotic properties of the error distribution estimation in right censored and sele...
Scientific congresses and symposiums : Unpublished conference
Physical, chemical, mathematical & earth Sciences : Mathematics
http://hdl.handle.net/2268/126350
Asymptotic properties of the error distribution estimation in right censored and selection biased regression models
English
Laurent, Géraldine mailto [Université de Liège - ULg > HEC-Ecole de gestion de l'ULg : UER > UER Opérations >]
Heuchenne, Cédric mailto [Université de Liège - ULg > HEC-Ecole de gestion de l'ULg : UER > Statistique appliquée à la gestion et à l'économie >]
16-Jun-2012
No
No
International
1st Conference of the International Society for NonParametric Statistics
15-19 June 2012
ISNPS
Chalkidiki
Greece
[en] nonparametric regression ; selection bias ; right censoring ; asymptotic properties
[en] Suppose the random vector (X,Y) satisfies the nonparametric regression model Y=m(X)+sigma(X)*epsilon where m(X) =E [Y|X] and sigma^2(X) = Var [Y|X] are unknown smooth functions and the error epsilon, with unknown distribution, is independent of the covariate X. The pair (X,Y) is subject to generalized bias selection and the response Y to right censoring. We define a new estimator for the cumulative distribution function of the error epsilon, where the estimators of m(.) and sigma^2(.) are obtained by extending the conditional estimation methods introduced in de Uña-Alvarez and Iglesias-Perez (2010). The asymptotic properties of the proposed estimator are established. A bootstrap technique is proposed to select the smoothing parameter involved in the procedure. Finally, this method is studied via extended simulations and applied to real data.
http://hdl.handle.net/2268/126350

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