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From Evan Ward <>
Subject Re: [math] fitting.leastsquares and stat.regression
Date Tue, 04 Mar 2014 19:37:54 GMT
Phil suggested we discuss the relationship of the two least squares
packages in [math]

Current Status

Currently both fitting.leastsquares and stat.regression have least
squares implementations. The fitting.leastsquares package supports
non-linear least squares with weights, pluggable optimization
algorithms, and (soon) data editing. The package is written from an
optimization/engineer's perspective.

As far as I can tell the stat.regression implementations are for linear
least squares. Some of the implementations contain neat optimizations,
for example requiring O(1) space for n data points. This package seems
to be written more from a statistician/economist's perspective.


1. Keep separate packages.
2. delegate the implementation from one package to the other
3. merge into a single package. (could lead to some interesting
algorithms. e.g. non-linear general least squares)

Phis, please add any important points I've missed.

Best Regards,

> Phil Steitz commented on MATH-1105:
> -----------------------------------
> Might be better to take this discussion to the ML. We now have two
> least squares impls - one in fitting/leastsquares and another in
> stats.regression (actually this has been true for some time). The
> stats side of it (residual analysis, ANOVA, etc.) belongs more
> naturally in stats.regression. It might make more sense to add this
> functionality there. Or maybe we just refactor to have the
> stats.regression classes use the impl in leastsquares. In any case, we
> should discuss on the ML.
>> Least squares statistical data editing
>> --------------------------------------
>> Key: MATH-1105
>> URL:
>> Project: Commons Math
>> Issue Type: Improvement
>> Reporter: Evan Ward
>> Attachments: 0001-Add-statistical-editing-capability.patch,
>> 0002-Integrate-data-editing-with-the-LS-framework.patch

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