Oberwolfach References on Mathematical Software

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Eviews supports general statistical analysis and econometric analyses (cross-section, panel data analysis, time series estimation and forecasting). It combines spreadsheet and relational database technology with the traditional tasks found in statistical software. Among its numerous data formats are Excel, databases, PSPP/SPSS, DAP/SAS, Stata, RATS, and TSP. Compatible: numerous formats, including databank format, Excel formats, PSPP/SPSS, DAP/SAS, Stata, RATS, and TSP

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HiFlow³ is a multi-purpose finite element software providing powerful tools for efficient and accurate solution of a wide range of problems modeled by partial differential equations. Based on object-oriented concepts and the full capabilities of C++ the HiFlow³ project follows a modular and generic approach for building efficient parallel numerical solvers. It provides highly capable modules dealing with the mesh setup, finite element spaces, degrees of freedom, linear algebra routines, numerical solvers, and output data for visualization. Parallelism – as the basis for high performance simulations on modern computing systems – is introduced on two levels: coarse-grained parallelism by means of distributed grids and distributed data structures, and fine-grained parallelism by means of platform-optimized linear algebra back-ends.

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The family of software packages for the econometric analysis of time series, forecasting, econometric model selection and for the statistical analysis of cross-section data and panel data.

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RATS (Regression Analysis of Time Series) is a fast, efficient, and comprehensive econometrics and time series analysis software package.

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The rbMIT © MIT software package implements in Matlab® all the general reduced basis algorithms. The rbMIT © MIT software package is intended to serve both (as Matlab® source) "Developers" — numerical analysts and computational tool-builders — who wish to further develop the methodology, and (as Matlab® "executables") "Users" — computational engineers and educators — who wish to rapidly apply the methodology to new applications. The rbMIT software package was awarded with the Springer Computational Science and Engineering Prize in 2009.

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