Uniform estimation of isobars
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
Uniform estimation of isobars
Author(s) :
Journal title :
Statistics and Probability Letters
Publisher :
Elsevier
Publication date :
2019-05
ISSN :
0167-7152
English keyword(s) :
order statistics
estimation
quantiles
strong behaviour
extremes
estimation
quantiles
strong behaviour
extremes
HAL domain(s) :
Mathématiques [math]
Statistiques [stat]
Statistiques [stat]
English abstract : [en]
The ordering of a multivariate sample is not natural and several definitions have been proposed in the literature. We consider here a multivariate sample ordered according to an increasing family of conditional quantile ...
Show more >The ordering of a multivariate sample is not natural and several definitions have been proposed in the literature. We consider here a multivariate sample ordered according to an increasing family of conditional quantile surfaces, isobar surfaces. We introduce a nonparametric estimator, called isogram, and establish the uniform a.s. consistency of these estimators. In particular, we show that, under some regularity conditions, the strong behaviour of the isograms is determined by the corresponding behaviour of suitable defined histogram-type estimators of the underlying conditional distribution function. Consequently, we begin our study by investigating the strong limiting behaviour of these estimators.Show less >
Show more >The ordering of a multivariate sample is not natural and several definitions have been proposed in the literature. We consider here a multivariate sample ordered according to an increasing family of conditional quantile surfaces, isobar surfaces. We introduce a nonparametric estimator, called isogram, and establish the uniform a.s. consistency of these estimators. In particular, we show that, under some regularity conditions, the strong behaviour of the isograms is determined by the corresponding behaviour of suitable defined histogram-type estimators of the underlying conditional distribution function. Consequently, we begin our study by investigating the strong limiting behaviour of these estimators.Show less >
Language :
Anglais
Popular science :
Non
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