Reference : Error distribution estimation in right censored and selection biased location-scale models
Scientific congresses and symposiums : Poster
Physical, chemical, mathematical & earth Sciences : Mathematics
http://hdl.handle.net/2268/118851
Error distribution estimation in right censored and selection biased location-scale 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 >]
23-Jun-2011
A5
No
No
International
Graybill Conference 2011
June 23-24, 2011
The Department of Statistics at Colorado State University
Fort Collins, Colorado
Colorado, United States
[en] nonparametric regression ; selection bias ; right censoring ; bandwidth selection ; asymptotic properties
[en] Suppose the random vector (X;Y) satis es the regression model Y = m(X)+sigma(X)*epsilon where m(X) = E[Y|X] and sigma²(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 selection biased and the response to right censoring. We construct a new estimator for the cumulative distribution function of the error epsilon, where the estimators of m(.) and sigma²(.) 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. This method is studied via extended simulations and applied to real unemployment data. Reference
de UNA-ALVAREZ, J., IGLESIAS-PEREZ, M.C. (2010): Nonparametric estimation of a conditional distribution from length-biased data. Annals of the Institute of Statistical Mathematics, Vol. 62, 323-341.
http://hdl.handle.net/2268/118851

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