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Inference for Heavy-Tailed Data

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Inference for Heavy-Tailed Data

Applications in Insurance and Finance

Liang Peng, Yongcheng Qi

Academic Press
Publication date : 2017-08-11

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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

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About the book

Author

Liang Peng , Yongcheng Qi

Imprint

Academic Press

Collection

n.c

Publication date

2017-08-11

Pages

180 pages

Print ISBN

9780128046760

Language

English

Ebook informations

EAN PDF

9780128047507

Price

£97.90

Copy count 18

Print count 18

File size 4393 Ko

Informations accessibility

EAN EPUB DRM-FREE

9780128047507

Price

£97.90

Informations accessibility

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About author(s)

Liang Peng

Yongcheng Qi

Dr Liang Peng is based at the Department of Risk Management and Insurance at Robinson College of Business, Georgia State University, USADr Yongcheng Qi is based at the Department of Mathematics and Statistics at the University of Minnesota, USA.

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