Fræser is a framework for estimating the parameters of static and dynamic errors-in-variables systems with the opportunity to compare various errors-in-variables parameter estimation algorithms via simulations. It features a graphical user interface and several examples for simultaneously estimating model and noise parameters.
The framework incorporates the following linear and nonlinear estimation methods for static and dynamic systems:
* model parameter estimation for static systems
o Koopmans method
* linear model and noise parameter estimation for dynamic systems
o (extended) instrumental variables method (XIV)
o bias-compensating least-squares method (BCLS)
o Frisch scheme (FS)
o generalized Koopmans-Levin method (GKL)
* nonlinear model parameter estimation for static systems
o nonlinear Koopmans method (NK)
o approximated maximum likelihood method (AML)
* nonlinear model and noise parameter estimation for dynamic systems
o bias-compensated least squares method (BCLS)
o nonlinear Koopmans-Levin method (NKL)
o nonlinear extennonlinear extension to generalized Koopmans-Levin method (NGKL)