Inference for Heavy Tailed Data

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  • Publisher : Academic Press
  • Release : 11 August 2017
  • ISBN : 9780128047507
  • Page : 180 pages
  • Rating : 4.5/5 from 103 voters

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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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Inference for Heavy-Tailed Data

Inference for Heavy-Tailed Data
  • Author : Liang Peng,Yongcheng Qi
  • Publisher : Academic Press
  • Release Date : 2017-08-11
  • ISBN : 9780128047507
GET THIS BOOKInference 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 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

Heavy-Tail Phenomena

Heavy-Tail Phenomena
  • Author : Sidney I. Resnick
  • Publisher : Springer Science & Business Media
  • Release Date : 2007-12-03
  • ISBN : 9780387450247
GET THIS BOOKHeavy-Tail Phenomena

This comprehensive text gives an interesting and useful blend of the mathematical, probabilistic and statistical tools used in heavy-tail analysis. It is uniquely devoted to heavy-tails and emphasizes both probability modeling and statistical methods for fitting models. Prerequisites for the reader include a prior course in stochastic processes and probability, some statistical background, some familiarity with time series analysis, and ability to use a statistics package. This work will serve second-year graduate students and researchers in the areas of applied

Nonparametric Analysis of Univariate Heavy-Tailed Data

Nonparametric Analysis of Univariate Heavy-Tailed Data
  • Author : Natalia Markovich
  • Publisher : John Wiley & Sons
  • Release Date : 2008-03-11
  • ISBN : 0470723599
GET THIS BOOKNonparametric Analysis of Univariate Heavy-Tailed Data

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

Heavy Tails And Copulas: Topics In Dependence Modelling In Economics And Finance

Heavy Tails And Copulas: Topics In Dependence Modelling In Economics And Finance
  • Author : Ibragimov Rustam,Prokhorov Artem
  • Publisher : World Scientific
  • Release Date : 2017-02-24
  • ISBN : 9789814689816
GET THIS BOOKHeavy Tails And Copulas: Topics In Dependence Modelling In Economics And Finance

This book offers a unified approach to the study of crises, large fluctuations, dependence and contagion effects in economics and finance. It covers important topics in statistical modeling and estimation, which combine the notions of copulas and heavy tails — two particularly valuable tools of today's research in economics, finance, econometrics and other fields — in order to provide a new way of thinking about such vital problems as diversification of risk and propagation of crises through financial markets due to contagion

A Practical Guide to Heavy Tails

A Practical Guide to Heavy Tails
  • Author : Robert Adler,Raya Feldman,Murad Taqqu
  • Publisher : Springer Science & Business Media
  • Release Date : 1998-10-26
  • ISBN : 0817639519
GET THIS BOOKA Practical Guide to Heavy Tails

Twenty-four contributions, intended for a wide audience from various disciplines, cover a variety of applications of heavy-tailed modeling involving telecommunications, the Web, insurance, and finance. Along with discussion of specific applications are several papers devoted to time series analysis, regression, classical signal/noise detection problems, and the general structure of stable processes, viewed from a modeling standpoint. Emphasis is placed on developments in handling the numerical problems associated with stable distribution (a main technical difficulty until recently). No index. Annotation

Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling

Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling
  • Author : Ivan Jeliazkov,Justin Tobias
  • Publisher : Emerald Group Publishing
  • Release Date : 2019-10-18
  • ISBN : 9781838674212
GET THIS BOOKTopics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling

Volume 40B of Advances in Econometrics examines innovations in stochastic frontier analysis, nonparametric and semiparametric modeling and estimation, A/B experiments, big-data analysis, and quantile regression.

Network Performance Engineering

Network Performance Engineering
  • Author : Demetres D. Kouvatsos
  • Publisher : Springer
  • Release Date : 2011-04-12
  • ISBN : 9783642027420
GET THIS BOOKNetwork Performance Engineering

During recent years a great deal of progress has been made in performance modelling and evaluation of the Internet, towards the convergence of multi-service networks of diverging technologies, supported by internetworking and the evolution of diverse access and switching technologies. The 44 chapters presented in this handbook are revised invited works drawn from PhD courses held at recent HETNETs International Working Conferences on Performance Modelling and Evaluation of Heterogeneous Networks. They constitute essential introductory material preparing the reader for further research

Heavy-Tailed Distributions and Robustness in Economics and Finance

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  • Author : Marat Ibragimov,Rustam Ibragimov,Johan Walden
  • Publisher : Springer
  • Release Date : 2015-05-23
  • ISBN : 9783319168777
GET THIS BOOKHeavy-Tailed Distributions and Robustness in Economics and Finance

This book focuses on general frameworks for modeling heavy-tailed distributions in economics, finance, econometrics, statistics, risk management and insurance. A central theme is that of (non-)robustness, i.e., the fact that the presence of heavy tails can either reinforce or reverse the implications of a number of models in these fields, depending on the degree of heavy-tailed ness. These results motivate the development and applications of robust inference approaches under heavy tails, heterogeneity and dependence in observations. Several recently

Handbook of Heavy Tailed Distributions in Finance

Handbook of Heavy Tailed Distributions in Finance
  • Author : S.T Rachev
  • Publisher : Elsevier
  • Release Date : 2003-03-05
  • ISBN : 0080557732
GET THIS BOOKHandbook of Heavy Tailed Distributions in Finance

The Handbooks in Finance are intended to be a definitive source for comprehensive and accessible information in the field of finance. Each individual volume in the series should present an accurate self-contained survey of a sub-field of finance, suitable for use by finance and economics professors and lecturers, professional researchers, graduate students and as a teaching supplement. The goal is to have a broad group of outstanding volumes in various areas of finance. The Handbook of Heavy Tailed Distributions in

Bayesian Inference

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  • Publisher : BoD – Books on Demand
  • Release Date : 2017-11-02
  • ISBN : 9789535135777
GET THIS BOOKBayesian Inference

The range of Bayesian inference algorithms and their different applications has been greatly expanded since the first implementation of a Kalman filter by Stanley F. Schmidt for the Apollo program. Extended Kalman filters or particle filters are just some examples of these algorithms that have been extensively applied to logistics, medical services, search and rescue operations, or automotive safety, among others. This book takes a look at both theoretical foundations of Bayesian inference and practical implementations in different fields. It

Extreme Events in Finance

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  • Publisher : John Wiley & Sons
  • Release Date : 2016-09-21
  • ISBN : 9781118650332
GET THIS BOOKExtreme Events in Finance

A guide to the growing importance of extreme value risk theory, methods, and applications in the financial sector Presenting a uniquely accessible guide, Extreme Events in Finance: A Handbook of Extreme Value Theory and Its Applications features a combination of the theory, methods, and applications of extreme value theory (EVT) in finance and a practical understanding of market behavior including both ordinary and extraordinary conditions. Beginning with a fascinating history of EVTs and financial modeling, the handbook introduces the historical

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  • Author : Patrice Bertail,Delphine Blanke,Pierre-André Cornillon,Eric Matzner-Løber
  • Publisher : Springer
  • Release Date : 2019-03-08
  • ISBN : 9783319969411
GET THIS BOOKNonparametric Statistics

This volume presents the latest advances and trends in nonparametric statistics, and gathers selected and peer-reviewed contributions from the 3rd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Avignon, France on June 11-16, 2016. It covers a broad range of nonparametric statistical methods, from density estimation, survey sampling, resampling methods, kernel methods and extreme values, to statistical learning and classification, both in the standard i.i.d. case and for dependent data, including big data. The International Society

Statistical Analysis of Financial Data

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  • Author : James Gentle
  • Publisher : CRC Press
  • Release Date : 2020-03-13
  • ISBN : 9780429939228
GET THIS BOOKStatistical Analysis of Financial Data

Statistical Analysis of Financial Data covers the use of statistical analysis and the methods of data science to model and analyze financial data. The first chapter is an overview of financial markets, describing the market operations and using exploratory data analysis to illustrate the nature of financial data. The software used to obtain the data for the examples in the first chapter and for all computations and to produce the graphs is R. However discussion of R is deferred to

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  • Publisher : John Wiley & Sons
  • Release Date : 2017-08-22
  • ISBN : 9781118595169
GET THIS BOOKStatistical Intervals

Describes statistical intervals to quantify sampling uncertainty,focusing on key application needs and recently developed methodology in an easy-to-apply format Statistical intervals provide invaluable tools for quantifying sampling uncertainty. The widely hailed first edition, published in 1991, described the use and construction of the most important statistical intervals. Particular emphasis was given to intervals—such as prediction intervals, tolerance intervals and confidence intervals on distribution quantiles—frequently needed in practice, but often neglected in introductory courses. Vastly improved computer capabilities over

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  • Author : Jayanta K. Ghosh,Mohan Delampady,Tapas Samanta
  • Publisher : Springer Science & Business Media
  • Release Date : 2007-07-03
  • ISBN : 9780387354330
GET THIS BOOKAn Introduction to Bayesian Analysis

This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory, methods, and applications. Starting from basic statistics, undergraduate calculus and linear algebra, ideas of both subjective and objective Bayesian analysis are developed to a level where real-life data can be analyzed using the current techniques of statistical computing. Advances in both low-dimensional and high-dimensional problems are covered, as well as important topics such as empirical Bayes and hierarchical Bayes methods and Markov chain Monte Carlo (MCMC) techniques. Many