Summary
International Symposium on Nonlinear Theory and its Applications
2010
Session Number:A1L-D
Session:
Number:A1L-D4
Rigorous parameter estimation for noisy mixed-effects models
Alexander Danis, Andrew Hooker, Warwick Tucker,
pp.67-70
Publication Date:2010/9/5
Online ISSN:2188-5079
DOI:10.34385/proc.44.A1L-D4
PDF download (107.4KB)
Summary:
We describe how constraint propagation techniques can be used to reliably reconstruct model parameters from noisy data. The main algorithm combines a branch and bound procedure with a data inflation step; it is robust and insensitive to noise. The set?valued results are transformed into point clouds, after which statistical properties can be retrieved. We apply the presented method to a mixed-effects model.