Copula-based Markov models for time series : parametric inference and process control

Copula-based Markov models for time series : parametric inference and process control / Li-Hsien Sun, Xin-Wei Huang, Mohammed S. Alqawba, Jong-Min Kim, Takeshi Emura.

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 tex...

Full description

Saved in:
Bibliographic Details
Main Authors: Sun, Li-Hsien (Author), Huang, Xin-Wei (Author), Alqawba, Mohammed S. (Author), Kim, Jong-min (Author), Emura, Takeshi (Author)
Format: eBook
Language:English
Published: Singapore : Springer, 2020.
Series:SpringerBriefs in statistics. JSS research series in statistics.
Subjects:
Copulas (Mathematical statistics)
Markov processes.
Time-series analysis.
Molecular biology.
Probability & statistics.
Science > Life Sciences > Anatomy & Physiology.
Mathematics > Probability & Statistics > General.
Business & Economics > Statistics.
Markov, Procesos de
Análisis de series temporales
Markov processes
Time-series analysis
Online Access:Click for online access
Table of Contents:
  • Chapter 1 Overview of the book with data examples.-Chapter 2 Copula and Markov models
  • Chapter 3 Estimation, model diagnosis, and process control under the normal model
  • Chapter 4 Estimation under the normal mixture model for financial time series data
  • Chapter 5 Bayesian estimation under the t-distribution for financial time series data
  • Chapter 6 Control charts of mean and variance using copula Markov SPC and conditional distribution by copula
  • Chapter 7 Copula Markov models for count series with excess zeros.

Similar Items