I am thinking along the following lines re organization of the initial
codebase for commonsmath(assuming we decide to move forward). Since I
am trying to refactor the various odds and ends that I have to
contribute along these lines, I would appreciate some feedback on the
structure. Obviously,this is a very preliminary "straw man." Any and
all ideas are welcome.
Highlevel organization

commonsmath
analysis
complex
discrete
linear
simulation
stat
Contents of the subpackages

Everything could probably initially be placed in one package, but I
would like to at least settle on a conceptual model for how things are
organized. It might also make sense in some cases to separate out an
"Impl" package for different implementation strategies.
analysis

Commonlyused univariate numerical analysis techniques and useful
formulas extending java.Math
Target for initial release:
* root finding
* polynomial interpolation
* error bounds estimation
* exponential growth and decay computations (set up for financial
applications)
complex

Representation and algebraic operations on complex numbers
Target for initial release:
* basic complex number class with algebraic operations
discrete

Basic methods and models from discrete math
Target for initial release:
* binomial coefficients
linear

Most commonly used numerical linear algebra techniques
Target for the initial release:
* basic real matrix class including algebraic operations and
support for solving linear systems
simulation

Mathematical tools to support simulation
Target for the initial release:
* Data generation class capable of generating random numbers
from uniform, gaussian, poisson, or exponential distributions; by
replaying data from an input file; by resampling from a vector; or by
generating random values from an empirical distribution
based on an input file.
stat

Commonlyused statistical techniques
Target for the initial release:
* Univariate  simple runningsums based univariate stats and
confidence intervals not requiring all data values to be stored in
memory and supporting a "rolling" capability (capability to base
statistics on most recently observed values)
* Frequencies  simple frequency counts/distribution.
* Regression  simple linear regression and bivariate corellation
* Tests  ttest, chisquare test
* Sampling  select random samples with/without replacement from
Collections
* Resampling  boostrap confidence intervals
Phil

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