Information Content in Data Sets: A Review of Methods for Interrogation and Model Comparison
In this reviewwe discuss methodology to ascertain the amount of information in given data sets with respect to determination of model parameters with desired levels of uncertainty.We do this in the context of least squares (ordinary,weighted, iterative reweightedweighted or "generalized", etc.) based inverse problem formulations. The ideas are illustrated with several examples of interest in the biological and environmental sciences.
Banks, H. Thomas; and Joyner, Michele L.. 2018. Information Content in Data Sets: A Review of Methods for Interrogation and Model Comparison. Journal of Inverse and Ill-Posed Problems. Vol.26(3). 423-452. https://doi.org/10.1515/jiip-2017-0096 ISSN: 0928-0219