The Shared Scientific Toolbox is a library that facilitates development of efficient, modular, and robust scientific/distributed computing applications in Java. It features multidimensional arrays with extensive linear algebra and FFT support, an asynchronous, scalable networking layer, and advanced class loading, message passing, and statistics packages.
superseriousstats is a small and efficient program for creating a Web page with statistics from various types of IRC logs. It keeps track of its parse history and only processes new activity before storing any accumulated data in a SQLite or MySQL database. It is suitable for high volume IRC channels and large log archives, and is relatively easy to integrate with IRC services (e.g. bots) that interact with the database and provide last seen information and many other statistics directly in your channel.
JoomlaWatch allows you to watch your Web site visitors and bots in real-time from the administration menu, particularly their IP addresses, countries they come from, geographical location on a map, which pages they are viewing, and their browser and operating system. It creates daily and all-time stats from this information plus unique, pageload, and total hits statistics. Furthermore, you can block harmful IP addresses, see blocked attempts stats, evaluate the trend charts, and create goals based on many parameters. In the frontend, it can show the top countries, user, and visit information for certain periods of time.
scikits.statsmodels is a Python package which provides a complement to scipy for statistical computations, including descriptive statistics and estimation of statistical models. The main included model categories are linear, discrete, generalized linear, and robust linear models, and, in time series analysis, AR, ARMA, and VAR. It also includes statistical tests mainly for regression diagnostics.
Isoline Retrieval uses supervised statistical classification to retrieve isolines from cross-track scanning or similar satellites. It contains software to generate training data using collocation or radiative transfer simulations, as well as routines to interpolate the final fields using a variation of multi-linear interpolation or kernel estimation. The currently-supported satellites are the Advance Microwave Sounding Unit (AMSU) series and, to a lesser extent, the Global Ozone Measurement Experiment (GOME). An ambitious researcher, however, could easily adapt the codes to a similar satellite.
statsmodels is a Python package which provides a complement to scipy for statistical computations, including descriptive statistics and estimation of statistical models. The main included model categories are linear, discrete, generalized linear, and robust linear, and, in time series analysis, AR, ARMA, and VAR. It also includes statistical tests mainly for regression diagnostics. statsmodels was renamed from scikits.statsmodels.