Basics of Applied Stochastic Processes
Stochastic processes are mathematical models of random phenomena that evolve according to prescribed dynamics. Processes commonly used in applications are Markov chains in discrete and continuous time, renewal and regenerative processes, Poisson processes, and Brownian motion. This volume gives an i...
| Main Author: | Serfozo, Richard (Author) |
|---|---|
| Corporate Author: | SpringerLink (Online service) |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2009.
|
| Series: | Probability and Its Applications,
|
| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
Similar Items
-
Stochastic Modeling
by: Lanchier, Nicolas
Published: (2017) -
Stochastic Geometry, Spatial Statistics and Random Fields Models and Algorithms /
Published: (2015) -
Potential Analysis of Stable Processes and its Extensions
by: Bogdan, Krzysztof, et al.
Published: (2009) -
Stochastic Analysis in Discrete and Continuous Settings With Normal Martingales /
by: Privault, Nicolas
Published: (2009) -
Stochastic Biomathematical Models with Applications to Neuronal Modeling /
Published: (2013)