The Library
Extending existing structural identifiability analysis methods to mixed-effects models
Tools
Tools
Tools
Janzén, David, Jirstrand, Mats, Chappell, M. J. (Michael J.) and Evans, Neil D. (2017) Extending existing structural identifiability analysis methods to mixed-effects models. Mathematical Biosciences, 295 . pp. 1-10. doi:10.1016/j.mbs.2017.10.009 ISSN 0025-5564.
|
PDF
WRAP-extending-existing-structural-analysis-models-Evans-2018.pdf - Accepted Version - Requires a PDF viewer. Download (1223Kb) | Preview |
Official URL: http://doi.org/10.1016/j.mbs.2017.10.009
Abstract
The concept of structural identifiability for state-space models is expanded to cover mixed-effects state-space models. Two methods applicable for the analytical study of the structural identifiability of mixed-effects models are presented. The two methods are based on previously established techniques for non-mixed-effects models; namely the Taylor series expansion and the input-output form approach. By generating an exhaustive summary, and by assuming an infinite number of subjects, functions of random variables can be derived which in turn determine the distribution of the system's observation function(s). By considering the uniqueness of the analytical statistical moments of the derived functions of the random variables, the structural identifiability of the corresponding mixed-effects model can be determined. The two methods are applied to a set of examples of mixed-effects models to illustrate how they work in practice. [Abstract copyright: Copyright © 2017 Elsevier Inc. All rights reserved.]
| Item Type: | Journal Article | ||||||
|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics | ||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||
| SWORD Depositor: | Library Publications Router | ||||||
| Library of Congress Subject Headings (LCSH): | Multilevel models (Statistics) , Series, Taylor's | ||||||
| Journal or Publication Title: | Mathematical Biosciences | ||||||
| Publisher: | Elsevier Science Inc. | ||||||
| ISSN: | 0025-5564 | ||||||
| Official Date: | 26 October 2017 | ||||||
| Dates: |
|
||||||
| Volume: | 295 | ||||||
| Page Range: | pp. 1-10 | ||||||
| DOI: | 10.1016/j.mbs.2017.10.009 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Reuse Statement (publisher, data, author rights): | ** From PubMed via Jisc Publications Router. ** History: received 04-04-2017; revised 04-08-2017; accepted 20-10-2017. | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Date of first compliant deposit: | 23 January 2018 | ||||||
| Date of first compliant Open Access: | 26 October 2018 | ||||||
| RIOXX Funder/Project Grant: |
|
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
