Title :

Estimating and forecasting periodically partially linear models with exogeneous Variables

Author(s) :

Brossat, Xavier [Auteur]
EDF [EDF]
Oppenheim, Georges [Auteur]
Laboratoire d'Analyse et de Mathématiques Appliquées [LAMA]
Viano, Marie-Claude [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]

Journal title :

Annales de l'ISUP

Pages :

55-82

Publisher :

Publications de l’Institut de Statistique de l’Université de Paris

Publication date :

2013

ISSN :

1626-1607

English keyword(s) :

a-mixing
additive models
autoregressive models
cyclostationarity
backfitting
electricity consumption
forecasting interval
semiparametric régression smoothing

HAL domain(s) :

Mathématiques [math]/Statistiques [math.ST]

English abstract : [en]

This paper presents a backfitting-type method for estimating and forecasting a periodically correlated partially linear model with exogeneous variables and heteroskedastic input noise, in the situation of hidden periodicity. ...
Show more >This paper presents a backfitting-type method for estimating and forecasting a periodically correlated partially linear model with exogeneous variables and heteroskedastic input noise, in the situation of hidden periodicity. A rate of convergence of the estimator is given.Show less >

Language :

Anglais

Popular science :

Non

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL