Book contents
- Frontmatter
- Contents
- 1 Introduction
- Part One Consistencies
- Part Two Structures
- 6 Strong Markov Family Structures
- 7 Markov Chain Structures
- 8 Conditional Markov Chain Structures
- 9 Special Semimartingale Structures
- Part Three Further Developments
- Part Four Applications of Stochastic Structures
- Appendices
- References
- Notation Index
- Subject Index
8 - Conditional Markov Chain Structures
from Part Two - Structures
Published online by Cambridge University Press: 18 September 2020
Book contents
- Frontmatter
- Contents
- 1 Introduction
- Part One Consistencies
- Part Two Structures
- 6 Strong Markov Family Structures
- 7 Markov Chain Structures
- 8 Conditional Markov Chain Structures
- 9 Special Semimartingale Structures
- Part Three Further Developments
- Part Four Applications of Stochastic Structures
- Appendices
- References
- Notation Index
- Subject Index
Summary
In this chapter we extend the theory of Markov structures from the universe of classical (finite) Markov chains to the universe of (finite) conditional Markov chains. As it turns out such extension is not a trivial one. But, it is quite important both from the mathematical point of view and from the practical point of view. We will first discuss the strong conditional Markov chain structures, and then we will study the concept of the weak conditional Markov chain structures.
- Type
- Chapter
- Information
- Structured Dependence between Stochastic Processes , pp. 108 - 116Publisher: Cambridge University PressPrint publication year: 2020