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)