Book contents
- Frontmatter
- Contents
- 1 Introduction
- Part One Consistencies
- 2 Strong Markov Consistency of Multivariate Markov Families and Processes
- 3 Consistency of Finite Multivariate Markov Chains
- 4 Consistency of Finite Multivariate Conditional Markov Chains
- 5 Consistency of Multivariate Special Semimartingales
- Part Two Structures
- Part Three Further Developments
- Part Four Applications of Stochastic Structures
- Appendices
- References
- Notation Index
- Subject Index
2 - Strong Markov Consistency of Multivariate Markov Families and Processes
from Part One - Consistencies
Published online by Cambridge University Press: 18 September 2020
- Frontmatter
- Contents
- 1 Introduction
- Part One Consistencies
- 2 Strong Markov Consistency of Multivariate Markov Families and Processes
- 3 Consistency of Finite Multivariate Markov Chains
- 4 Consistency of Finite Multivariate Conditional Markov Chains
- 5 Consistency of Multivariate Special Semimartingales
- Part Two Structures
- Part Three Further Developments
- Part Four Applications of Stochastic Structures
- Appendices
- References
- Notation Index
- Subject Index
Summary
In this chapter the concept of strong Markov consistency for multivariate Markov families and for multivariate Markov processes is introduced and studied. Strong Markov consistency of a multivariate Markov family/process, if satisfied, provides for invariance of the Markov property under coordinate projections, a property that is important in various practical applications. We only consider conservative Markov processes and Markov families.In Section 2.1, we study the so-called strong Markov consistency for multivariate Markov families and multivariate Markov processes taking values in an arbitrary metric space. This study is geared towards formulating a general framework within which the strong Markov consistency can be conveniently analyzed. In Section 2.2, we specify our study of the strong Markov consistency to the case of multivariate Feller-Markov families taking values in Rn. The analysis is first carried in the time-inhomogeneous case, and then in the time homogeneous case where a more comprehensive study can be done.
- Type
- Chapter
- Information
- Structured Dependence between Stochastic Processes , pp. 7 - 37Publisher: Cambridge University PressPrint publication year: 2020