Result: Numerical solution of stochastic differential problems in the biosciences
Title:
Numerical solution of stochastic differential problems in the biosciences
Authors:
Source:
International Workshop on the Technological Aspects of MathematicsJournal of computational and applied mathematics. 185(2):422-440
Publisher Information:
Amsterdam: Elsevier, 2006.
Publication Year:
2006
Physical Description:
print, 18 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Probabilités et statistiques, Probability and statistics, Théorie des probabilités et processus stochastiques, Probability theory and stochastic processes, Analyse stochastique, Stochastic analysis, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Equations algébriques et transcendantes non linéaires, Nonlinear algebraic and transcendental equations, Probabilités et statistiques numériques, Numerical methods in probability and statistics, Sciences biologiques et medicales, Biological and medical sciences, Sciences biologiques fondamentales et appliquees. Psychologie, Fundamental and applied biological sciences. Psychology, Generalites, General aspects, Mathématiques biologiques. Statistiques. Modèles. Métrologie. Informatique en biologie (généralités), Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects), Analyse numérique, Numerical analysis, Análisis numérico, Biologie mathématique, Mathematical biology, Biología matemática, Dynamique population, Population dynamics, Dinámica población, Epidémiologie, Epidemiology, Epidemiología, Equation différentielle, Differential equation, Ecuación diferencial, Equation intégrale, Integral equation, Ecuación integral, Equation stochastique, Stochastic equation, Ecuación estocástica, Equation à retard, Delay equation, Ecuación retardada, Extrapolation, Extrapolación, Mathématiques appliquées, Applied mathematics, Matemáticas aplicadas, Modèle mathématique, Mathematical model, Modelo matemático, Méthode Runge Kutta, Runge Kutta method, Método Runge Kutta, Méthode multipas, Multistep method, Método multipaso, Méthode numérique, Numerical method, Método numérico, Solution numérique, Numerical solution, Equation différentielle stochastique, Méthode Euler, 60H10, 65C20, 65H35, 92D25 Stochastic ordinary differential equations, Biomathematical modelling, Numerical methods for stochastic equations, Stochastic delay differential equations
Document Type:
Conference
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Istituto di Biomatematica, Località Crocicchia, 61029 Urbino (PU), Italy
ISSN:
0377-0427
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Biological sciences. Generalities. Modelling. Methods
Generalities in biological sciences
Mathematics
Generalities in biological sciences
Mathematics
Accession Number:
edscal.17186259
Database:
PASCAL Archive
Further Information
Stochastic differential equations (SDEs) models play a prominent role in many application areas including biology, epidemiology and population dynamics, mostly because they can offer a more sophisticated insight through physical phenomena than their deterministic counterparts do. So, suitable numerical methods must be introduced to simulate the solutions of the resulting stochastic differential systems. In this work we take into account both Euler-Taylor expansion and Runge-Kutta-type methods for stochastic ordinary differential equations (SODEs) and the Euler-Maruyama method for stochastic delay differential equations (SDDEs), focusing on the most relevant implementation issues. The corresponding Matlab codes for both SODEs and SDDEs problems are tested on mathematical models arising in the biosciences.