Copula-Based Markov Models for Time Series

Li-Hsien Sun

ISBN 10: 9811549974 / ISBN 13: 9789811549977

Published by Springer, Palgrave Macmillan Jul 2020, 2020

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -This book provides statistical methodologies for time series data, focusing on copula-based Markov chain models for serially correlated time series. It also includes data examples from economics, engineering, finance, sport and other disciplines to illustrate the methods presented. An accessible textbook for students in the fields of economics, management, mathematics, statistics, and related fields wanting to gain insights into the statistical analysis of time series data using copulas, the book also features stand-alone chapters to appeal to researchers.As the subtitle suggests, the book highlights parametric models based on normal distribution, t-distribution, normal mixture distribution, Poisson distribution, and others. Presenting likelihood-based methods as the main statistical tools for fitting the models, the book details the development of computing techniques to find the maximum likelihood estimator. It also addresses statistical process control, as well as Bayesian and regression methods. Lastly, to help readers analyze their data, it provides computer codes (R codes) for most of the statistical methods.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 148 pp. Englisch.

Seller Inventory # 9789811549977

Bibliographic Details

• Title: Copula-Based Markov Models for Time Series
• Publisher: Springer, Palgrave Macmillan Jul 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 9811549974
• ISBN 13: 9789811549977
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 9D millimeters 235 millimeters width by 155 millimeters height by 9 millimeters depth
• Weight: 236 grams

About this title

Synopsis

This book provides statistical methodologies for time series data, focusing on copula-based Markov chain models for serially correlated time series. It also includes data examples from economics, engineering, finance, sport and other disciplines to illustrate the methods presented. An accessible textbook for students in the fields of economics, management, mathematics, statistics, and related fields wanting to gain insights into the statistical analysis of time series data using copulas, the book also features stand-alone chapters to appeal to researchers.

As the subtitle suggests, the book highlights parametric models based on normal distribution, t-distribution, normal mixture distribution, Poisson distribution, and others. Presenting likelihood-based methods as the main statistical tools for fitting the models, the book details the development of computing techniques to find the maximum likelihood estimator. It also addresses statistical process control, as well as Bayesian and regression methods. Lastly, to help readers analyze their data, it provides computer codes (R codes) for most of the statistical methods.

About the Author

Li-Hsien Sun,  National Central University

Xin-Wei Huang, National Chiao Tung University

Mohammed S. Alqawba, Qassim University

Jong-Min Kim, University of Minnesota at Morris

Takeshi Emura, Chang Gung University