[Estimation non paramétrique d'une tendance à partir de réalisations d'un processus à temps continu]
Soit X= un processus aléatoire du second ordre dont on observe n réalisations indépendantes sur une grille de p points déterministes. Sous de faibles conditions de régularité sur les trajectoires de X, nous prouvons la normalité asymptotique d'estimateurs non paramétriques de la tendance dans l'espace lorsque , puis nous obtenons des bandes de confiance simultanées approchées pour μ à l'aide de la théorie des processus Gaussiens.
Let be a second order random process of which n independent realizations are observed on a fixed grid of p time points. Under mild regularity assumptions on the sample paths of X, we show the asymptotic normality of suitable nonparametric estimators of the trend function in the space as and, using Gaussian process theory, we derive approximate simultaneous confidence bands for μ.
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David Degras 1
@article{CRMATH_2009__347_3-4_191_0, author = {David Degras}, title = {Nonparametric estimation of a trend based upon sampled continuous processes}, journal = {Comptes Rendus. Math\'ematique}, pages = {191--194}, publisher = {Elsevier}, volume = {347}, number = {3-4}, year = {2009}, doi = {10.1016/j.crma.2008.12.016}, language = {en}, }
David Degras. Nonparametric estimation of a trend based upon sampled continuous processes. Comptes Rendus. Mathématique, Volume 347 (2009) no. 3-4, pp. 191-194. doi : 10.1016/j.crma.2008.12.016. https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.1016/j.crma.2008.12.016/
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