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Distribution theory of runs and patterns and its applications : a finite Markov chain imbedding approach /
A rigorous, comprehensive introduction to the finite Markov chain imbedding technique for studying the distributions of runs and patterns from a unified and intuitive viewpoint, away from the lines of traditional combinatorics. The central theme of this approach is to properly imbed the random varia...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
River Edge, N.J. :
World Scientific,
©2003.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Preface ; Chapter 1 Introduction ; Chapter 2 Finite Markov Chain Imbedding ; 2.1 Finite Markov Chain ; 2.2 Chapman-Kolmogorov Equation ; 2.3 Tree-Structured Markov Chain ; 2.4 Runs and Patterns ; 2.5 Finite Markov Chain Imbedding ; 2.6 Absorbing State.
- 2.7 First-Entry Probability Chapter 3 Runs and Patterns in a Sequence of Two-State Trials ; 3.1 Introduction ; 3.2 Number of Non-Overlapping Consecutive k Successes ; 3.3 Number of Success Runs of Length Greater Than or Equal to k ; 3.4 Number of Overlapping Consecutive k Successes.
- 3.5 Number of Runs of Exactly k Successes 3.6 The Distribution of the Longest Success Run ; 3.7 Waiting-Time Distribution of a Success Run ; 3.8 Numerical Examples ; 3.9 Number of Successes in Success Runs of Length Greater Than or Equal to k.
- Chapter 4 Runs and Patterns in Multi-State Trials 4.1 Introduction ; 4.2 Forward and Backward Principle with Non-Overlap Counting ; 4.3 Overlap Counting ; 4.4 Series Pattern ; 4.5 Joint Distribution ; Chapter 5 Waiting-Time Distributions ; 5.1 Introduction.
- 5.2 The Waiting Time of A Simple Pattern 5.3 The Waiting Time of A Compound Pattern ; 5.4 Probability Generating Function ; 5.5 Mean of Waiting Time W(A) ; 5.6 More About Generating Functions ; 5.7 Spectrum Analysis and Large Deviation Approximation.