Green’s matching: an efficient approach to parameter estimation in complex dynamic systems
dc.contributor.author | Tan, Jianbin | |
dc.contributor.author | Zhang, Guoyu | |
dc.contributor.author | Wang, Xueqin | |
dc.contributor.author | Huang, Hui | |
dc.contributor.author | Yao, Fang | |
dc.date.accessioned | 2024-04-13T04:32:55Z | |
dc.date.available | 2024-04-13T04:32:55Z | |
dc.description.abstract | <jats:title>Abstract</jats:title> <jats:p>Parameters of differential equations are essential to characterize intrinsic behaviours of dynamic systems. Numerous methods for estimating parameters in dynamic systems are computationally and/or statistically inadequate, especially for complex systems with general-order differential operators, such as motion dynamics. This article presents Green’s matching, a computationally tractable and statistically efficient two-step method, which only needs to approximate trajectories in dynamic systems but not their derivatives due to the inverse of differential operators by Green’s function. This yields a statistically optimal guarantee for parameter estimation in general-order equations, a feature not shared by existing methods, and provides an efficient framework for broad statistical inferences in complex dynamic systems.</jats:p> | |
dc.identifier.issn | 1369-7412 | |
dc.identifier.issn | 1467-9868 | |
dc.identifier.uri | ||
dc.language | en | |
dc.publisher | Oxford University Press (OUP) | |
dc.relation.ispartof | Journal of the Royal Statistical Society Series B: Statistical Methodology | |
dc.relation.isversionof | 10.1093/jrsssb/qkae031 | |
dc.rights.uri | ||
dc.title | Green’s matching: an efficient approach to parameter estimation in complex dynamic systems | |
dc.type | Journal article | |
duke.contributor.orcid | Tan, Jianbin|0000-0002-3264-1086 | |
pubs.organisational-group | Duke | |
pubs.organisational-group | School of Medicine | |
pubs.organisational-group | Staff | |
pubs.organisational-group | Basic Science Departments | |
pubs.organisational-group | Biostatistics & Bioinformatics | |
pubs.organisational-group | Biostatistics & Bioinformatics, Division of Translational Biomedical | |
pubs.publication-status | Published online |