Stochastic modeling / Nicolas Lanchier.
Material type:
TextSeries: UniversitextPublication details: Cham : Springer, 2017.Description: xiii, 303 pages : illustrations (some color) ; 24 cmISBN: - 9783319500379
- 519.23 23 L248
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 519.23 L248 (Browse shelf(Opens below)) | Available | 138298 |
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| 519.23 L237 stochastic processes | 519.23 L237 stochastic processes | 519.23 L237 stochastic processes | 519.23 L248 Stochastic modeling / | 519.23 L334 Probability models in engineering sciences | 519.23 L334 Probability models in engineering sciences | 519.23 L352 Stochastic processes applied to physics and other related fields |
Includes bibliographical references and index.
1. Basics of Measure and Probability Theory.-
2. Distribution and Conditional Expectation.-
3. Limit Theorems.-
4. Stochastic Processes: General Definition.-
5. Martingales.-
6. Branching Processes.-
7. Discrete-time Markov Chains.-
8. Symmetric Simple Random Walks.-
9. Poisson Point and Poisson Processes.-
10. Continuous-time Markov Chains.-
11. Logistic Growth Process.-
12. Wright-Fisher and Moran Models.-
13. Percolation Models.-
14. Interacting Particle Systems.-
15. The Contact Process.-
16. The Voter Model.-
17. Numerical Simulations in C and Matlab.
Additional emphasis is placed on minimal models that have been used historically to develop new mathematical techniques in the field of stochastic processes: the logistic growth process, the Wright -Fisher model, Kingman's coalescent, percolation models, the contact process, and the voter model.
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