title: Forcing function diagnostics for nonlinear dynamics.
abstract: This article investigates the problem of model diagnostics for systems described by nonlinear ordinary differential equations (ODEs). I propose modeling lack of fit as a time-varying correction to the right-hand side of a proposed differential equation. This correction can be described as being a set of additive forcing functions, estimated from data. Representing lack of fit in this manner allows us to graphically investigate model inadequacies and to suggest model improvements. I derive lack-of-fit tests based on estimated forcing functions. Model building in partially observed systems of ODEs is particularly difficult and I consider the problem of identification of forcing functions in these systems. The methods are illustrated with examples from computational neuroscience.
authors.affiliation: Department of Biological Statistics and Nonlinear Dynamics, Cornell University, Ithaca, New York 14850, USA. giles.hooker@cornell.edu
authors.forename: Giles
authors.initials: G
authors.lastname: Hooker
mesh_terms: D001699:Biometry / Q000379:methods*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D008954:Models, Biological; D017711:Nonlinear Dynamics