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Established in 1996, the Journal of Statistical Software publishes articles, book reviews, code snippets, and software reviews on the subject of statistical software and algorithms. The contents are freely available on-line. For both articles and code snippets the source code is published along with the paper.
Statistical software is the key link between statistical methods and their application in practice. Software that makes this link is the province of the journal, and may be realized as, for instance, tools for large scale computing, database technology, desktop computing, distributed systems, the World Wide Web, reproducible research, archiving and documentation, and embedded systems.
We attempt to present research that demonstrates the joint evolution of computational and statistical methods and techniques. Implementations can use languages such as C, C++, S, Fortran, Java, PHP, Python and Ruby or environments such as Mathematica, MATLAB, R, S-PLUS, SAS, Stata, and XLISP-STAT.
1 Numerical Optimization in R-Beyond optim.pdf
(182.09 KB)
2 On Best Practice Optimization Methods in R.pdf
(280.91 KB)
3 Spectral Projected Gradient Methods-Review and Perspectives.pdf
(760.2 KB)
4 trustOptim-An R Package for Trust Region Optimization with Sparse Hessians.pdf
(395.01 KB)
5 Convex Optimization in R.pdf
(377.05 KB)
6 Continuous Global Optimization in R.pdf
(807.7 KB)
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