You can also access our individual websites (via the Members page) for further information about our research and lists of our publications.
@article{Beguerisse-Díaz:2012:10.1098/rsif.2011.0767,
author = {Beguerisse-Díaz, M and Wang, B and Desikan, R and Barahona, M},
doi = {10.1098/rsif.2011.0767},
journal = {Journal of The Royal Society Interface},
title = {Squeeze-and-breathe evolutionary Monte Carlo optimization with local search acceleration and its application to parameter fitting},
url = {http://dx.doi.org/10.1098/rsif.2011.0767},
year = {2012}
}
TY - JOUR
AB - Estimating parameters from data is a key stage of the modelling process, particularly in biological systems where many parameters need to be estimated from sparse and noisy datasets. Over the years, a variety of heuristics have been proposed to solve this complex optimization problem, with good results in some cases yet with limitations in the biological setting. In this work, we develop an algorithm for model parameter fitting that combines ideas from evolutionary algorithms, sequential Monte Carlo and direct search optimization. Our method performs well even when the order of magnitude and/or the range of the parameters is unknown. The method refines iteratively a sequence of parameter distributions through local optimization combined with partial resampling from a historical prior defined over the support of all previous iterations. We exemplify our method with biological models using both simulated and real experimental data and estimate the parameters efficiently even in the absence of a priori knowledge about the parameters.
AU - Beguerisse-Díaz,M
AU - Wang,B
AU - Desikan,R
AU - Barahona,M
DO - 10.1098/rsif.2011.0767
PY - 2012///
TI - Squeeze-and-breathe evolutionary Monte Carlo optimization with local search acceleration and its application to parameter fitting
T2 - Journal of The Royal Society Interface
UR - http://dx.doi.org/10.1098/rsif.2011.0767
UR - http://rsif.royalsocietypublishing.org/content/early/2012/01/18/rsif.2011.0767.abstract
UR - http://hdl.handle.net/10044/1/10372
ER -