EASY-FIT ModelDesign 5.0

The system solves constrained nonlinear parameter estimation (nonlinear regression, data, curve and surface fitting) problems based on ODEs, DAEs, PDEs, PDAEs, steady-state systems, Laplace equations, and analytical functions.
A statistical analysis provides confidence intervals, correlation and covariance matrix, identification of significant parameters, and allows optimum experimental design.
Model equations are defined in a modeling language called PCOMP and are interpreted and evaluated during runtime.
General: Arbitrary fitting criteria depending on the solution of a dynamical system, e.g., of a differential equation, and the parameters to be estimated; additional nonlinear equality or inequality constraints, second independent model variable called concentration Numerical routines: Gauss-Newton-type SQP methods for least squares optimization, implicit ODE/DAE solver, method-of-lines for 1D PDEs, automatic differentiation, alternative norms (sum of absolute values, maximum of absolute values) , confidence intervals for estimated parameters, correlation and covariance matrix, identification of significance levels for estimated parameters User interface: Convenient and flexible modeling language, 'find' and 'filter' commands, report and graphics facilities, also for Gnuplot, 3D plots for two model or input variables (surface fitting), in- and output of data from and to text or Excel files Limitations: 30 fitting criteria and data sets, 500 differential equations, 100 algebraic equations, 50 PDEs (1D), 100 model variables, 2,000 time values, 3,000 experimental data, 200 linear or nonlinear constraints Modeling language (PCOMP) : Highly flexible statements depending on parameters to be estimated, tabulated data, splines, linear and piecewise constant interpolation Implementation: Numerical routines in Fortran executable outside of the GUI, GUI in VBA, Microsoft Access 2007 run-time version included