Random First-Order Linear Discrete Models and Their Probabilistic Solution: A Comprehensive Study

This paper presents a complete stochastic solution represented by the first probability density function for random first-order linear difference equations. The study is based on Random Variable Transformation method. The obtained results are given in terms of the probability density functions of the data, namely, initial condition, forcing term, and diffusion coefficient. To conduct the study, all possible cases regarding statistical dependence of the random input parameters are considered. A complete collection of illustrative examples covering all the possible scenarios is provided.

[1]  Juan Carlos Cortés,et al.  Solving initial and two-point boundary value linear random differential equations: A mean square approach , 2012, Appl. Math. Comput..

[2]  M. Abramowitz,et al.  Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables (National Bureau of Standards Applied Mathematics Series No. 55) , 1965 .

[3]  M. El-Beltagy,et al.  Higher-Order WHEP Solutions of Quadratic Nonlinear Stochastic Oscillatory Equation , 2013 .

[4]  E. Allen Modeling with Itô Stochastic Differential Equations , 2007 .

[5]  Daoyi Xu,et al.  Mean square exponential stability of impulsive stochastic difference equations , 2007, Appl. Math. Lett..

[6]  K. Nouri,et al.  Mean Square Convergence of the Numerical Solution of Random Differential Equations , 2015 .

[7]  Noha A. Al-Mulla,et al.  Solution of the Stochastic Heat Equation with Nonlinear Losses Using Wiener-Hermite Expansion , 2014, J. Appl. Math..

[9]  Carlos A. Braumann,et al.  Growth and extinction of populations in randomly varying environments , 2008, Comput. Math. Appl..

[10]  S. Zacks,et al.  Introduction to stochastic differential equations , 1988 .

[11]  P. Kloeden,et al.  Numerical Solution of Stochastic Differential Equations , 1992 .

[12]  M. M. Selim,et al.  A developed solution of the stochastic Milne problem using probabilistic transformations , 2010, Appl. Math. Comput..

[13]  Mohamed A. El-Beltagy,et al.  Numerical Approximation of Higher-Order Solutions of the Quadratic Nonlinear Stochastic Oscillatory Equation Using WHEP Technique , 2013, J. Appl. Math..

[14]  M. El-Tawil,et al.  A proposed technique of SFEM on solving ordinary random differential equation , 2005, Appl. Math. Comput..

[15]  Juan Carlos Cortés López,et al.  Determining the first probability density function of linear random initial value problems by the Random Variable Transformation (RVT) technique: A comprehensive study , 2014 .

[16]  N. Bershad,et al.  Random differential equations in science and engineering , 1975, Proceedings of the IEEE.

[17]  S. Aachen Stochastic Differential Equations An Introduction With Applications , 2016 .

[18]  R. Ghanem,et al.  Stochastic Finite Elements: A Spectral Approach , 1990 .

[19]  D. Rajan Probability, Random Variables, and Stochastic Processes , 2017 .

[20]  W. Enders Applied Econometric Time Series , 1994 .

[21]  Juan Carlos Cortés,et al.  Random matrix difference models arising in long-term medical drug strategies , 2010, Appl. Math. Comput..

[22]  M. M. Selim,et al.  Solution of the stochastic transport equation of neutral particles with anisotropic scattering using RVT technique , 2009, Appl. Math. Comput..

[23]  A. Hussein,et al.  Using FEM-RVT technique for solving a randomly excited ordinary differential equation with a random operator , 2007, Appl. Math. Comput..

[24]  Magdy A. El-Tawil,et al.  The approximate solutions of some stochastic differential equations using transformations , 2005, Appl. Math. Comput..

[25]  M. M. Selim,et al.  Solution of the stochastic radiative transfer equation with Rayleigh scattering using RVT technique , 2012, Appl. Math. Comput..

[26]  R. H. Myers,et al.  STAT 319 : Probability & Statistics for Engineers & Scientists Term 152 ( 1 ) Final Exam Wednesday 11 / 05 / 2016 8 : 00 – 10 : 30 AM , 2016 .