Gaussx provides for linear and non-linear optimization with and without parameter constraints. For example, ols y c x1 x2 ĭoes ordinary least squares, while mcmc z1 c z3 z4 ĭoes a Bayesian estimation of a Tobit model using Markov Chain Monte Carlo. Gaussx provides an environment that makes econometric programming a joy. Alternatively, since the GAUSS source is included, individual econometric routines can be extracted and integrated in stand-alone GAUSS programs. These tools can be used within Gaussx, both in research and in teaching. Gaussx incorporates a full-featured set of professional state-of-the-art econometric routines that run under GAUSS.
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