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- Kobayashi, Hisashi.
- Cambridge ; New York : Cambridge University Press, 2011.
1 online resource.
- Stochastic analysis.
- Machine generated contents note: 1. Introduction; Part I. Probability, Random Variables and Statistics: 2. Probability; 3. Discrete random variables; 4. Continuous random variables; 5. Functions of random variables and their distributions; 6. Fundamentals of statistical analysis; 7. Distributions derived from the normal distribution; Part II. Transform Methods, Bounds and Limits: 8. Moment generating function and characteristic function; 9. Generating function and Laplace transform; 10. Inequalities, bounds and large deviation approximation; 11. Convergence of a sequence of random variables, and the limit theorems; Part III. Random Processes: 12. Random process; 13. Spectral representation of random processes and time series; 14. Poisson process, birth-death process, and renewal process; 15. Discrete-time Markov chains; 16. Semi-Markov processes and continuous-time Markov chains; 17. Random walk, Brownian motion, diffusion and it's processes; Part IV. Statistical Inference: 18. Estimation and decision theory; 19. Estimation algorithms; Part V. Applications and Advanced Topics: 20. Hidden Markov models and applications; 21. Probabilistic models in machine learning; 22. Filtering and prediction of random processes; 23. Queuing and loss models.
- Description based on print version record.
Electronic reproduction. Palo Alto, Calif. Available via World Wide Web.
- Local notes:
- Acquired for the Penn Libraries with assistance from the Class of 1891 Department of Arts Fund.
Mark, Brian L. (Brian Lai-bue), 1969-
Class of 1891 Department of Arts Fund.
- Other format:
- Print version: Probability, random processes, and statistical analysis.
- 1139185691 (electronic bk.)
9781139185691 (electronic bk.)
- Publisher no.:
- Web link:
The Class of 1891 Department of Arts Fund Home Page
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