GaussFit

GaussFit is a software package designed for nonlinear least-squares fitting and data analysis. It enables researchers to fit mathematical models to experimental data, estimate model parameters, and assess the reliability of the results. The program is widely used in fields such as physics, chemistry, biology, and engineering to extract quantitative information from measurements.

Users provide a model expressed as an algebraic equation involving parameters and independent variables, along with data sets and optional measurement uncertainties. GaussFit then applies iterative optimization methods, commonly Gauss-Newton and Levenberg-Marquardt, to minimize the weighted sum of squared residuals. It reports parameter estimates with standard errors and a covariance matrix, as well as confidence intervals and correlation among parameters. The software also produces goodness-of-fit metrics, residual plots, and diagnostic information to evaluate model adequacy. In addition to single-model fits, GaussFit supports multiple data sets and global fitting, and offers options for robust fitting and outlier handling.

Data input is typically ASCII text files containing independent-variable values, dependent measurements, and optional weights. Output includes a structured report summarizing the fit, a parameter table, and plots or plot-ready data for further analysis. The program is available for several platforms and can be used via a command-line interface or a graphical front end, depending on the distribution, with accompanying documentation and examples.

Since its development, GaussFit has been cited in scholarly literature as a practical tool for nonlinear regression and error analysis, helping researchers quantify relationships in experimental data and evaluate uncertainties in parameter estimates.