Nonparametric Analysis of Univariate Heavy-Tailed Data 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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Markovich, Natalia 作者

译者

2007-12 出版日期

336 页数

940.00元价格

丛书系列

9780470510872 图书编码

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Nonparametric Analysis of Univariate Heavy-Tailed Data 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

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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.

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