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.
<p> 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</p><p> 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</p><p> 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 </p><p> 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</p><p> Modeling language (PCOMP) : Highly flexible statements depending on parameters to be estimated, tabulated data, splines, linear and piecewise constant interpolation</p><p> Implementation: Numerical routines in Fortran executable outside of the GUI, GUI in VBA, Microsoft Access 2007 run-time version included</p>