Software

Software by Jurgen A Doornik

Oxmetrics is a family of of software packages providing an integrated solution for the econometric analysis of time series, forecasting, financial econometric modelling, or statistical analysis of cross-section and panel data. OxMetrics consists of a front-end program called OxMetrics, and individual application modules such as PcGive, STAMP, etc. OxMetrics Enterprise is a single product that includes all the important components: OxMetrics desktop, G@RCH, Ox Professional, PcGive and STAMP.

Ox is an object-oriented statistical system. At its core is a powerful matrix language, which is complemented by a comprehensive statistical library. Among the special features of Ox are its speed, well-designed syntax and editor, and graphical facilities. Ox can read and write many data formats, including spreadsheets and OxMetrics files; Ox can run most econometric Gausstm programs. Ox comes in two versions: Ox Professional and Ox Console. Ox is available for Windows, Linux, Mac (OS X), and several Unix platforms.

PcGive Professional aims to give an operational and structured approach to econometric modelling using the most sophisticated yet user-friendly software. The accompanying books transcend the old ideas of `textbooks' and `computer manuals' by linking the learning of econometric methods and concepts to the outcomes achieved when they are applied. The econometric techniques of PcGive include: VAR, cointegration, simultaneous equations models, Markov Switching, ARFIMA, logit, probit, GARCH modelling, static and dynamic panel data models, X12ARIMA, and more. PcGive uses Autometrics for automatic model selection.

OxEdit is an easy to use, yet powerful text editor. Its support for syntax highlighting, column editing, and running external tools make it especially useful for developing and running Ox programs. OxEdit is installed with Ox Console, but can be downloaded separately for Windows.

Software by Tom Snijders

SIENA is a program for the statistical analysis of longitudinal network data, with the focus on social networks. Its implementation as an R package is called Rsiena and allows a variety of types of network data structures.
The research team is composed of Tom Snijders, Christian Steglich, Ruth Ripley, Johan Koskinen, and Krists Boitmanis, with contributions from Michael Schweinberger, Mark Huisman, Marijtje van Duijn, and others.