Monotonous continuous-time random walks with drift and stochastic reset events
| Autor: | Miquel Montero, Javier Villarroel |
|---|---|
| Přispěvatelé: | Universitat de Barcelona |
| Rok vydání: | 2012 |
| Předmět: |
Monte Carlo method
FOS: Physical sciences Monotonic function Probability density function Transformació de Laplace Stochastic processes Econometrics FOS: Mathematics Computer Simulation Statistical physics Mètode de Montecarlo Mathematical Physics Mathematics Models Statistical Laplace transformation Reset (finance) Stochastic process Probability (math.PR) Processos estocàstics Mathematical Physics (math-ph) Random walk Action (physics) Constant (mathematics) Monte Carlo Method Mathematics - Probability Algorithms |
| Zdroj: | Dipòsit Digital de la UB Universidad de Barcelona Recercat. Dipósit de la Recerca de Catalunya instname |
| DOI: | 10.48550/arxiv.1206.4570 |
| Popis: | In this paper we consider a stochastic process that may experience random reset events which bring suddenly the system to the starting value and analyze the relevant statistical magnitudes. We focus our attention on monotonous continuous-time random walks with a constant drift: the process increases between the reset events, either by the effect of the random jumps, or by the action of the deterministic drift. As a result of all these combined factors interesting properties emerge, like the existence|for any drift strength|of a stationary transition probability density function, or the faculty of the model to reproduce power-law-like behavior. General formulas for two extreme statistics, the survival probability and the mean exit time, are also derived. To corroborate in an independent way the results of the paper, Monte Carlo methods were used. These numerical estimations are in full agreement with the analytical predictions. Comment: 15 pages, 4 figures, revtex4-1; considerable revision, 4 appendices added |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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