STATISTICAL INFERENCE ON FRACTIONAL
ADVECTION-DIFFUSION TRANSPORT SYSTEMS
Edward Boone1, Ryad Ghanam2
1Department of Statistical Sciences
and Operations Research
Virginia Commonwealth University
Richmond, VA 23284, USA
2Department of Liberal Arts and Sciences
Virginia Commonwealth University in Qatar
Doha, QATAR

Abstract

The field fractional partial differential equations has been greatly expanding with in the last 20 years as evidenced by the growing body of literature. The work has primarily been theoretical in nature as there has been limited availability of experimental data. This work demonstrates using simulated data, how one can utilize these models and apply them to real world data to make inferences about the parameter values, predictions at future values and even what forcing mechanism was used to generate the data. This is done using a Bayesian approach that employs Markov chain Monte Carlo techniques. The proposed approach is evaluated using simulation studies concerning credible interval coverage probabilities and highest posterior model probabilities. The simulation study shows that the proposed method is effective for many parameters and that more work is needed to better estimate some physical coefficients.

Citation details of the article



Journal: International Journal of Applied Mathematics
Journal ISSN (Print): ISSN 1311-1728
Journal ISSN (Electronic): ISSN 1314-8060
Volume: 36
Issue: 1
Year: 2023

DOI: 10.12732/ijam.v36i1.11
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