A parameter-free model comparison test using differential algebra

Author: 

Harrington, H
Ho, K
Meshkat, N

Publication Date: 

17 February 2019

Journal: 

Complexity

Last Updated: 

2020-02-18T14:35:54.07+00:00

Volume: 

2019

DOI: 

10.1155/2019/6041981

abstract: 

We present a method for rejecting competing models from noisy time-course data that does not rely on parameter inference. First we characterize ordinary differential equation models in only measurable variables using differential-algebra elimination. This procedure gives input-output equations, which serve as invariants for time series data. We develop a model comparison test using linear algebra and statistics to reject incorrect models from their invariants. This algorithm exploits the dynamic properties that are encoded in the structure of the model equations without recourse to parameter values, and, in this sense, the approach is parameter-free. We demonstrate this method by discriminating between different models from mathematical biology.

Symplectic id: 

953154

Submitted to ORA: 

Submitted

Publication Type: 

Journal Article