Questions about mathematical and statistical functionality in Python
topkatz at msn.com
Thu Jun 14 23:02:01 CEST 2007
I hope you'll indulge an ignorant outsider. I work at a financial software
firm, and the tool I currently use for my research is R, a software
environment for statistical computing and graphics. R is designed with
matrix manipulation in mind, and it's very easy to do regression and time
series modeling, and to plot the results and test hypotheses. The kinds of
functionality we rely on the most are standard and robust versions of
regression and principal component / factor analysis, bayesian methods such
as Gibbs sampling and shrinkage, and optimization by linear, quadratic,
newtonian / nonlinear, and genetic programming; frequently used graphics
include QQ plots and histograms. In R, these procedures are all available
as functions (some of them are in auxiliary libraries that don't come with
the standard distribution, but are easily downloaded from a central
For a variety of reasons, the research group is considering adopting Python.
Naturally, I am curious about the mathematical, statistical, and graphical
functionality available in Python. Do any of you out there use Python in
financial research, or other intense mathematical/statistical computation?
Can you compare working in Python with working in a package like R or S-Plus
or Matlab, etc.? Which of the procedures I mentioned above are available in
Python? I appreciate any insight you can provide. Thanks!
-- TMK --
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