Inference for Heavy Tailed Data

This book PDF is perfect for those who love Mathematics genre, written by Liang Peng and published by Academic Press which was released on 11 August 2017 with total hardcover pages 180. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Inference for Heavy Tailed Data books below.

Inference for Heavy Tailed Data
Author : Liang Peng
File Size : 45,6 Mb
Publisher : Academic Press
Language : English
Release Date : 11 August 2017
ISBN : 9780128047507
Pages : 180 pages
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Inference for Heavy Tailed Data by Liang Peng Book PDF Summary

Heavy tailed data appears frequently in social science, internet traffic, insurance and finance. Statistical inference has been studied for many years, which includes recent bias-reduction estimation for tail index and high quantiles with applications in risk management, empirical likelihood based interval estimation for tail index and high quantiles, hypothesis tests for heavy tails, the choice of sample fraction in tail index and high quantile inference. These results for independent data, dependent data, linear time series and nonlinear time series are scattered in different statistics journals. Inference for Heavy-Tailed Data Analysis puts these methods into a single place with a clear picture on learning and using these techniques. Contains comprehensive coverage of new techniques of heavy tailed data analysis Provides examples of heavy tailed data and its uses Brings together, in a single place, a clear picture on learning and using these techniques

Inference for Heavy Tailed Data

Heavy tailed data appears frequently in social science, internet traffic, insurance and finance. Statistical inference has been studied for many years, which includes recent bias-reduction estimation for tail index and high quantiles with applications in risk management, empirical likelihood based interval estimation for tail index and high quantiles, hypothesis tests

Get Book
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