DataStatix manages data of every kind, creates statistics and graphs, and exports data easily to the R environment. Its features include user management (create, delete, modify password) within the software, different levels of user data access (administrator, standard, read-only), user-defined templates (models) of data, the ability to create new databases easily, importation and exportation of data in CSV format, and synchronization of existing data from a CSV file created with DataStatix.
RCaller is a Java library for calling R commands and scripts from Java. It sends text scripts to the R interpreter and converts the results to XML using the R package ~Ruinversal~. After this, the XML document is parsed to convert those results to Java arrays and matrices. RCaller has support for external source files with external functions and plots.
SWATnalysis is a utility that runs the Soil and Water Assessment Tool (SWAT) and analyzes its output files. It converts archaically formatted SWAT output files into more user friendly CSV files, performs graphical analysis, calculates area weighted precipitation values, and performs statistical analysis of observed data versus simulated data.
SWIG is a software development tool that connects programs written in C and C++ with a variety of high-level programming languages. SWIG is primarily used with common scripting languages such as Perl, PHP, Python, Tcl/Tk, and Ruby, however the list of supported languages also includes non-scripting languages such as C#, Common Lisp (CLISP, Allegro CL, UFFI), Java, Modula-3, OCAML, Octave, and R. Also several interpreted and compiled Scheme implementations (Guile, MzScheme, Chicken) are supported. SWIG is most commonly used to create high-level interpreted or compiled programming environments, user interfaces, and as a tool for testing and prototyping C/C++ software. SWIG can also export its parse tree in the form of XML and Lisp s-expressions.
Strategico is an engine for running statistical analysis over groups of time series. It can manage one or more groups (projects) of time series: by default, you can get data from a database or CSV files, normalize them, and then save them inside the engine. The first statistical analysis implemented inside Strategico is the "Long Term Prediction": it automatically finds the best model that fits each time series. Some of the models implemented are mean, trend, linear, exponential smoothing, and Arima. Strategico is scalable: the statistical analysis over each time series (of a project) can be run separately and independently. It is suggested that you set up an HPC Cluster (High Performance Computing) and/or use a resource scheduler like slurm. It is developed with R, one of the most famous statistical languages.