Literature DB >> 25574073

Model Comparison Tests to Determine Data Information Content.

H T Banks1, J E Banks2, Kathryn Link1, J A Rosenheim3, Chelsea Ross1, K A Tillman1.   

Abstract

In the context of inverse or parameter estimation problems we demonstrate the use of statistically based model comparison tests in several examples of practical interest. In these examples we are interested in questions related to information content of a particular given data set and whether the data will support a more complicated model to describe it. In the first example we compare fits for several different models to describe simple decay in a size histogram for aggregates in amyloid fibril formation. In a second example we investigate whether the information content in data sets for the pest Lygus hesperus in cotton fields as it is currently collected is sufficient to support a model in which one distinguishes between nymphs and adults. Finally in a third example with data for patients having undergone an organ transplant, we question whether the data content is sufficient to estimate more than 5 of the fundamental parameters in a particular dynamic model.

Entities:  

Keywords:  Ordinary least squares; information content; model comparison in inverse problems

Year:  2015        PMID: 25574073      PMCID: PMC4283942          DOI: 10.1016/j.aml.2014.11.002

Source DB:  PubMed          Journal:  Appl Math Lett        ISSN: 0893-9659            Impact factor:   4.055


  3 in total

1.  Estimation and prediction with HIV-treatment interruption data.

Authors:  B M Adams; H T Banks; M Davidian; E S Rosenberg
Journal:  Bull Math Biol       Date:  2007-01-09       Impact factor: 1.758

2.  Uncertainty quantification in modeling HIV viral mechanics.

Authors:  H T Banks; Robert Baraldi; Karissa Cross; Kevin Flores; Christina McChesney; Laura Poag; Emma Thorpe
Journal:  Math Biosci Eng       Date:  2015-10       Impact factor: 2.080

3.  Modelling HIV immune response and validation with clinical data.

Authors:  H T Banks; M Davidian; Shuhua Hu; Grace M Kepler; E S Rosenberg
Journal:  J Biol Dyn       Date:  2008-10       Impact factor: 2.179

  3 in total
  1 in total

1.  Information content in data sets for a nucleated-polymerization model.

Authors:  H T Banks; Marie Doumic; Carola Kruse; Stephanie Prigent; Human Rezaei
Journal:  J Biol Dyn       Date:  2015-06-05       Impact factor: 2.179

  1 in total

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