Hi, having managed to write the documentation for it I just released a new version of Sci - a library for general purpose scientific computing (MIT licensed). It's composed of the following modules: sci.math: special mathematical functions sci.diff: automatic differentiation sci.alg: vector and matrix algebra sci.quad: quadrature algorithms sci.root: root-finding algorithms sci.fmin: function minimization algorithms sci.fmax: function maximization algorithms sci.prng: pseudo random number generators sci.qrng: quasi random number generators sci.stat: statistical functions sci.dist: statistical distributions sci.mcmc: MCMC algorithms At the same time I updated all my other libraries (Xsys, Time, LJSQLite3, Rclient) and released a new version of the LuaJIT Universal Package for LuaJIT 2.0.3 which as usual supports Windows, Linux, OS X and bundles a number of system libraries. Thanks to the luapower developer(s) who inspired some simplifying changes. To avoid confusion I numbered all libraries as 1.0-beta4. As usual, everything is available for download at: http://www.scilua.org/ I would suggest to just decompress everything into a new directory and move there your personal libraries / work. As it proved to be a popular request I have created Git repositories for all the libraries: https://github.com/stepelu It's the first time I use Github, so if you spot something which is clearly wrong please let me know and I'll fix it. As I know that there are a number of users around who tired my libraries I would really appreciate some feedback / features requests. In particular, the sci.alg module (definitely the most complex one) is the outcome of a number of re-writes. I added a short implementation documentation in the file in case someone is interested to have a peek. Expect the following features to appear in the next relase(s): + faster forward-mode automatic differentiation: I have implemented a prototype which requires a single traversal of the function, around 30-40% faster in typical multivariate scenarios. Then backward-mode automatic differentiation... + multivariate statistical distributions: uniform, normal, student, dirichlet, copula + BFGS optimizer + higher-level BLAS/Lapack-based matrix algebra routines I'll be traveling in the next month hence my replies could be delayed. Stefano