Copula-Based Markov Models for Time Series Parametric Inference and Process Control
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...
| Main Authors: | , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Singapore
Springer Nature Singapore
2020, 2020
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| Edition: | 1st ed. 2020 |
| Series: | JSS Research Series in Statistics
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
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