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GaussFit was developed as a platform to facilitate the solution of least squares and robust estimation problems for astrometric data reduction with data from the NASA Hubble Space Telescope. An environment where astrometric models could easily and quickly be written, tested and modified was required. GaussFit is capable of handling situations that arise often enough to be of practical interest, but which have usually been ignored because they are not well understood by many users. It provides an easy and natural way to formulate general nonlinear problems; problems where the observation equations (equations of condition) contain more than one observation (the errors-in-variables case); problems with correlated observations; problems where exact constraints among parameters must be enforced. Certain robust estimation methods that generalize least squares to non-euclidian metrics and provide greater immunity against RoutliersS than does the classical least squares method are available. GaussFit runs both under UNIX and VMS and there is a Macintosh version.
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