Abstract and Applied Analysis

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

M.-C. Casabán, J.-C. Cortés, J.-V. Romero, and M.-D. Roselló

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Abstract

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.

Article information

Source
Abstr. Appl. Anal., Volume 2016 (2016), Article ID 6372108, 22 pages.

Dates
Received: 3 October 2015
Accepted: 1 February 2016
First available in Project Euclid: 19 May 2016

Permanent link to this document
https://projecteuclid.org/euclid.aaa/1463662620

Digital Object Identifier
doi:10.1155/2016/6372108

Mathematical Reviews number (MathSciNet)
MR3490100

Zentralblatt MATH identifier
06929383

Citation

Casabán, M.-C.; Cortés, J.-C.; Romero, J.-V.; Roselló, M.-D. Random First-Order Linear Discrete Models and Their Probabilistic Solution: A Comprehensive Study. Abstr. Appl. Anal. 2016 (2016), Article ID 6372108, 22 pages. doi:10.1155/2016/6372108. https://projecteuclid.org/euclid.aaa/1463662620


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