Abstract
Dynamic Energy Budget (DEB) theory constitutes a coherent set of universal biological processes that have been used as building blocks for modeling biological systems over the last 40 years in many applied disciplines. In the context of extracting parameters for DEB models from data, we discuss the methodology of fitting multiple models, which share parameters, to multiple data sets in a single parameter estimation. This problem is not specific to DEB models, and is (or should be) really general in biology. We discovered that a lot of estimation problems that we suffered from in the past originated from the use of a loss function that was not symmetric in the role of data and predictions. We here propose two much better symmetric candidates, that proved to work well in practice. We illustrate estimation problems and their solutions with a Monte-Carlo case study for increasing amount of scatter, which decreased the amount of information in the data about one or more parameter values. We here validate the method using a set of models with known parameters and different scatter structures. We compare the loss functions on the basis of convergence, point and interval estimates. We also discuss the use of pseudo-data, i.e. realistic values for parameters that we treat as data from which predictions can differ. These pseudo-data are used to avoid that a good fit results in parameter values that make no biological sense. We discuss our new method for estimating confidence intervals and present a list of concrete recommendations for parameter estimation. We conclude that the proposed method performs very well in recovering parameter values of a set of models, applied to a set of data. This is consistent with our large-scale applications in practice.
Original language | English |
---|---|
Pages (from-to) | 48-56 |
Number of pages | 9 |
Journal | Journal of sea research |
Volume | 143 |
Early online date | 9 Jul 2018 |
DOIs | |
Publication status | Published - Jan 2019 |
Funding
We want to thank the 125 contributors of the Add-my-Pet collection for their hard work and the hundreds of Dynamic Energy Budget theory course participants for guiding us to problems in methods and code that needed to be solved. This work was supported by The Research Council of Norway, grant no. 255295 (Framework for integrating Eco-physiological and Eco-toxicological data into ecosystem-based management tools). We further thank two anonymous referees and M. R. Kearney (guest editor of this special issue on DEB) whose helpful comments improved the Ms.
Funders | Funder number |
---|---|
The Research Council of Norway | |
Norges forskningsråd | 255295 |
Keywords
- Fitting models
- Interval estimates
- Loss function
- Monte Carlo simulation studies
- Parameter estimation
- Point estimates
Fingerprint
Dive into the research topics of 'Fitting multiple models to multiple data sets'. Together they form a unique fingerprint.Datasets
-
Data for: Fitting Multiple Models to Multiple Data Sets
Augustine, S. (Contributor), Marques, G. (Contributor), Lika, K. (Contributor), Pecquerie, L. (Contributor) & Kooijman, B. (Contributor), Unknown Publisher, 18 Jul 2018
DOI: 10.17632/6s77pb7fxk.1, https://data.mendeley.com/datasets/6s77pb7fxk
Dataset / Software: Dataset