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Expectile asymptotics

Authors: Holzmann, H.; Klar, B.;

Expectile asymptotics

Abstract

We discuss in detail the asymptotic distribution of sample expectiles. First, we show uniform consistency under the assumption of a finite mean. In case of a finite second moment, we show that for expectiles other then the mean, only the additional assumption of continuity of the distribution function at the expectile implies asymptotic normality, otherwise, the limit is non-normal. For a continuous distribution function we show the uniform central limit theorem for the expectile process. If, in contrast, the distribution is heavy-tailed, and contained in the domain of attraction of a stable law with $1 < ��< 2$, then we show that the expectile is also asymptotically stable distributed. Our findings are illustrated in a simulation section.

Country
Germany
Related Organizations
Keywords

ddc:510, convergence to stable distributions, FOS: Computer and information sciences, Asymptotic distribution theory in statistics, asymptotic normality, Infinitely divisible distributions; stable distributions, Central limit and other weak theorems, M-estimator, 510, Methodology (stat.ME), uniform central limit theorem, expectiles, Mathematics, info:eu-repo/classification/ddc/510, Statistics - Methodology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
33
Top 10%
Top 10%
Top 10%
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gold