TY  - JOUR
N1  - cited By 2
SN  - 10762787
N2  - 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. © 2017 Ahmed A. Mahmoud et al.
Y1  - 2017///
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042188211&doi=10.1155%2f2017%2f6148934&partnerID=40&md5=9568e7daabd10ab4739960792c2bfd9a
ID  - scholars9072
JF  - Complexity
AV  - none
A1  - Mahmoud, A.A.
A1  - Dass, S.C.
A1  - Muthuvalu, M.S.
A1  - Asirvadam, V.S.
TI  - Maximum Likelihood Inference for Univariate Delay Differential Equation Models with Multiple Delays
PB  - Hindawi Limited
VL  - 2017
ER  -