cl-statistics
numerical-utilities
| cl-statistics | numerical-utilities | |
|---|---|---|
| 1 | 2 | |
| 3 | 13 | |
| - | - | |
| 0.0 | 5.5 | |
| almost 2 years ago | 5 months ago | |
| Common Lisp | Common Lisp | |
| - | Microsoft Public License |
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cl-statistics
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Uncle Stats Wants You
I don't know if it would be helpful in making this new statistics library, but I have just taken my (slightly) updated copy of Larry Hunter's cl-statistics library and put it on Ghithub here: https://github.com/rpgoldman/cl-statistics
numerical-utilities
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Uncle Stats Wants You
Refresh the histogram code. Tamas Papp has a lot of good code that needs dusting off. The histogram code has a some bitrot that can be easily cleaned up and would make a nice addition. See the bottom of the statistics.lisp file.
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New Lisp-Stat Release
I think this depends on what part of the statistics universe you're working in.
For example, within Lisp-Stat the statistics routines [1] were written by an econometrician working for the Austrian government (Julia folks might know him - Tamas Papp). It would not be exaggerating to say his job depending on it. These are state of the art, high performance algorithms, equal to anything available in R or Python. So, if you're doing econometrics, or something related, everything you need is already there in the tin.
For machine learning, there's CLML [2], developed by NTT. This is the largest telco in Japan, equivalent to ATT in the USA. As well, there is MGL [3], used to win the Higgs Boson challenge a few years back. Both actively maintained.
For linear algebra, MagicCL was mention elsewhere in the thread. My favourite is MGL-MAT [4], also by the author of MGL. This supports both BLAS and CUBLAS (CUDA for GPUs) for solutions.
Finally, there's the XLISP-STAT archive [5]. Prior to Luke Tierney, the author of XLISP-Stat joining the core R team, XLISP-STAT was the dominate statistical computing platform. There's heaps of stuff in the archive, most at least as good as what's in base R, that could be ported to Lisp-Stat.
Common Lisp is a viable platform for statistics and machine learning. It isn't (yet) quite as well organised as R or Python, but it's all there.
[1] https://github.com/Lisp-Stat/numerical-utilities/blob/master...
What are some alternatives?
plot - A vega-lite DSL for Common Lisp
clml - Common Lisp Machine Learning Library
data-frame - Data frames for Common Lisp
ultralisp - The software behind a Ultralisp.org Common Lisp repository
magicl - Matrix Algebra proGrams In Common Lisp.
cephes.cl - Wrapper for the Cephes Mathematical Library
mgl - Common Lisp machine learning library.
xls-archive - Statistics routines in Common Lisp and XLispStat
incanter - Clojure-based, R-like statistical computing and graphics environment for the JVM
mgl-mat - MAT is library for working with multi-dimensional arrays which supports efficient interfacing to foreign and CUDA code. BLAS and CUBLAS bindings are available.