Téléchargez le livre : Nonparametric Analysis of Univariate Heavy-Tailed Data

Nonparametric Analysis of Univariate Heavy-Tailed Data

Research and Practice de

Éditeur :

Wiley-Interscience


Collection :

Wiley Series in Probability and Statistics

Paru le : 2008-03-11

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Description
Heavy-tailed distributions are typical for phenomena in complex multi-component systems such as biometry, economics, ecological systems, sociology, web access statistics, internet traffic, biblio-metrics, finance and business. The analysis of such distributions requires special methods of estimation due to their specific features. These are not only the slow decay to zero of the tail, but also the violation of Cramer’s condition, possible non-existence of some moments, and sparse observations in the tail of the distribution.
The book focuses on the methods of statistical analysis of heavy-tailed independent identically distributed random variables by empirical samples of moderate sizes. It provides a detailed survey of classical results and recent developments in the theory of nonparametric estimation of the probability density function, the tail index, the hazard rate and the renewal function.
Both asymptotical results, for example convergence rates of the estimates, and results for the samples of moderate sizes supported by Monte-Carlo investigation, are considered. The text is illustrated by the application of the considered methodologies to real data of web traffic measurements.
Pages
336 pages
Collection
Wiley Series in Probability and Statistics
Parution
2008-03-11
Marque
Wiley-Interscience
EAN papier
9780470510872
EAN PDF
9780470723593
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
336
Taille du fichier
4813 Ko
Prix
126,55 €

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