Inference for Heavy-Tailed Data

Applications in Insurance and Finance

Nonfiction, Science & Nature, Mathematics, Applied
Cover of the book Inference for Heavy-Tailed Data by Liang Peng, Yongcheng Qi, Elsevier Science
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Liang Peng, Yongcheng Qi ISBN: 9780128047507
Publisher: Elsevier Science Publication: August 11, 2017
Imprint: Academic Press Language: English
Author: Liang Peng, Yongcheng Qi
ISBN: 9780128047507
Publisher: Elsevier Science
Publication: August 11, 2017
Imprint: Academic Press
Language: English

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
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Elsevier Science

Cover of the book Rockbolting by Liang Peng, Yongcheng Qi
Cover of the book Hip Disorders in Children by Liang Peng, Yongcheng Qi
Cover of the book Handbook of Silicon Based MEMS Materials and Technologies by Liang Peng, Yongcheng Qi
Cover of the book Understanding Satellite Navigation by Liang Peng, Yongcheng Qi
Cover of the book A Guide to the Manufacture, Performance, and Potential of Plastics in Agriculture by Liang Peng, Yongcheng Qi
Cover of the book Pharmaceutics by Liang Peng, Yongcheng Qi
Cover of the book Comprehensive Structural Integrity by Liang Peng, Yongcheng Qi
Cover of the book Genetics and Evolution of Infectious Diseases by Liang Peng, Yongcheng Qi
Cover of the book Handbook of Coastal Disaster Mitigation for Engineers and Planners by Liang Peng, Yongcheng Qi
Cover of the book Shared Earth Modeling by Liang Peng, Yongcheng Qi
Cover of the book Radioactivity in the Environment by Liang Peng, Yongcheng Qi
Cover of the book Fluorine in Life Sciences: Pharmaceuticals, Medicinal Diagnostics, and Agrochemicals by Liang Peng, Yongcheng Qi
Cover of the book Overview of Industrial Process Automation by Liang Peng, Yongcheng Qi
Cover of the book Corrosion of Metallic Heritage Artefacts by Liang Peng, Yongcheng Qi
Cover of the book Spatially Resolved Operando Measurements in Heterogeneous Catalytic Reactors by Liang Peng, Yongcheng Qi
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy