Maximum Likelihood Inference for Univariate Delay Differential Equation Models with Multiple Delays. (12th October 2017)

• Record Type: Journal Article
• Authors: Mahmoud, Ahmed A.; Dass, Sarat C.; Muthuvalu, Mohana S.; Asirvadam, Vijanth S.
• Other Names: Rihan Fathalla A. Academic Editor.
• Is Part Of: Complexity. Volume 2017(2017)
• Publication Date: 2017-10-12
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2017/6148934
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : This article presents statistical inference methodology based on maximum likelihoods for delay differential equation models in the univariate setting. Maximum likelihood inference is obtained for single and multiple unknown delay parameters as well as other parameters of interest that govern the trajectories of the delay differential equation models. The maximum likelihood estimator is obtained based on adaptive grid and Newton-Raphson algorithms. Our methodology estimates correctly the delay parameters as well as other unknown parameters (such as the initial starting values) of the dynamical system based on simulation data. We also develop methodology to compute the information matrix and confidence intervals for all unknown parameters based on the likelihood inferential framework. We present three illustrative examples related to biological systems. The computations have been carried out with help of mathematical software: MATLAB® 8.0 R2014b.