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

Joint Authors

Cortés López, Juan Carlos
Casabán, M.-C.
Romero, J.-V.
Roselló, M.-D.

Source

Abstract and Applied Analysis

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-22, 22 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-04-11

Country of Publication

Egypt

No. of Pages

22

Main Subjects

Mathematics

Abstract EN

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.

American Psychological Association (APA)

Casabán, M.-C.& Cortés López, Juan Carlos& Romero, J.-V.& Roselló, M.-D.. 2016. Random First-Order Linear Discrete Models and Their Probabilistic Solution: A Comprehensive Study. Abstract and Applied Analysis،Vol. 2016, no. 2016, pp.1-22.
https://search.emarefa.net/detail/BIM-1094764

Modern Language Association (MLA)

Casabán, M.-C.…[et al.]. Random First-Order Linear Discrete Models and Their Probabilistic Solution: A Comprehensive Study. Abstract and Applied Analysis No. 2016 (2016), pp.1-22.
https://search.emarefa.net/detail/BIM-1094764

American Medical Association (AMA)

Casabán, M.-C.& Cortés López, Juan Carlos& Romero, J.-V.& Roselló, M.-D.. Random First-Order Linear Discrete Models and Their Probabilistic Solution: A Comprehensive Study. Abstract and Applied Analysis. 2016. Vol. 2016, no. 2016, pp.1-22.
https://search.emarefa.net/detail/BIM-1094764

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1094764