Stochastic versus deterministic systems of iterative processes
Stochastic systems of difference equations with random parameters methods -- Stochastic systems of difference equations of Ito-type-methods -- Stochastic systems of difference equations-qualitative analysis -- Random polynomials -- Numerical schemes for systems of differential equations with random...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Weitere Verfasser: | |
| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
New Jersey, London, Singapore, Beijing, Shanghai, Hong Kong, Taipei, Chennai, Tokyo
World Scientific
2024
|
| Schriftenreihe: | Trends in abstract and applied analysis
volume 11 |
| Schlagworte: | |
| Online Zugang: | Inhaltsverzeichnis |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Tag hinzufügen | Zusammenfassung: | Stochastic systems of difference equations with random parameters methods -- Stochastic systems of difference equations of Ito-type-methods -- Stochastic systems of difference equations-qualitative analysis -- Random polynomials -- Numerical schemes for systems of differential equations with random parameters -- Numerical schemes for systems of difference equations of Ito-type -- Discrete-time probabilistic, stochastic dynamic modeling, and statistical data analyses. "State continuous dynamic models can be reformulated into discrete state processes. This process generates numerical schemes that lead theoretical iterative schemes. This type of method of stochastic modelling generates three basic problems. First, the fundamental properties of solution, namely, existence, uniqueness, measurability, continuous dependence on system parameters depend mode of convergence. Second, the basic probabilistic and statistical properties mean, variance, moments of qualitative/quantitative behaviour of solutions are directly described as concept of solution process or via probability distribution or density functions either. Finally, deterministic versus stochastic modelling of dynamic processes is to what extent the stochastic mathematical model differs from the corresponding deterministic model in the absence of random disturbances or fluctuations and uncertainties. Most literature in this subject was developed in the 1950s, and focussed on the theory of systems of continuous and discrete-time deterministic; however, continuous-time and its approximation schemes of stochastic differential equations faced the problems outlined above and made slow progress in developing problems as a result. This monograph addresses these problems by presenting an account of stochastic versus deterministic issues in discrete state dynamic systems in a systematic and unified way"-- |
|---|---|
| Beschreibung: | Literaturverzeichnis: Seite 333-337 |
| Beschreibung: | xi, 342 Seiten |
| ISBN: | 9789811287473 978-981-12-8747-3 |