Probability, random processes, and statistical analysis
"Together with the fundamentals of probability, random processes and statistical analysis, this insightful book also presents a broad range of advanced topics and applications. There is extensive coverage of Bayesian vs. frequentist statistics, time series and spectral representation, inequalities,...
সংরক্ষণ করুন:
| প্রধান লেখক: | |
|---|---|
| সংস্থা লেখক: | |
| অন্যান্য লেখক: | , |
| বিন্যাস: | বৈদ্যুতিক বৈদ্যুতিন গ্রন্থ |
| ভাষা: | ইংরেজি |
| প্রকাশিত: |
Cambridge ; New York :
Cambridge University Press,
2012.
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| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | An electronic book accessible through the World Wide Web; click to view |
| ট্যাগগুলো: |
কোনো ট্যাগ নেই, প্রথমজন হিসাবে ট্যাগ করুন!
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সূচিপত্রের সারণি:
- 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.