Gretl 1.9.4

Gretl is a powerful software package designed for econometric analysis. Developed by Allin Cottrell, Riccardo Lucchetti, and the gretl team, this cross-platform, open-source tool is a must-have for statisticians and econometricians.

With an easy-to-use interface and support for multiple languages, Gretl simplifies the process of analyzing statistics and econometrics data. It offers a wide range of estimator functions, including GMM, least squares, maximum likelihood, and system methods, allowing users to infer unknown parameter values in statistical models.

Gretl also provides time series indexing methods such as ARIMA, univariate GARCH-type models, Kalman filter, structural VARs and VECMs, unit-root and cointegration tests. This enables users to index data in time order and analyze the relationships between variables.

In addition, Gretl supports limited dependent variables like interval regression, logit, models for count and duration data, probit, sample selection, and tobit. These methods are essential for estimating the connection between the limited dependent variable being observed and other variables with set parameters.

One of Gretl's standout features is its compatibility with other statistical tools. It can be integrated with various add-ons and contributed function packages, enriching the user experience and expanding the capabilities of the software. Gretl also includes a custom scripting language called hansl, which automates repetitive tasks and allows users to create procedures implementing techniques and special functions.

With Gretl, users can easily create fine-tuned Gnuplot graphs and exchange data and results with other programming languages like GNU R, Julia, Octave, Ox, Python, and Stata. The software also supports parallelization via MPI and offers compatibility with the Mixed Data Sampling approach (MIDAS) and the Library for Support Vector Machines (LIBSVM) machine learning library.

Overall, Gretl is a comprehensive and versatile tool for econometric analysis. Its open-source nature and compatibility with other statistical tools make it a valuable asset for researchers, analysts, and students in the field of economics.