[Rd] application to mentor syrfr package development for Google Summer of Code 2010
jsalsman at talknicer.com
Mon Mar 8 06:00:27 CET 2010
If I understand your concern, you want to lay the foundation for
derivatives so that you can implement the search strategies described
in Schmidt and Lipson (2010) --
http://www.springerlink.com/content/l79v2183725413w0/ -- is that
right? It is not clear to me how well this generalized approach will
work in practice, but there is no reason not to proceed in parallel to
establish a framework under which you could implement the metrics
proposed by Schmidt and Lipson in the contemplated syrfr package.
I have expanded the test I proposed with two more questions -- at
5. Critique http://sites.google.com/site/gptips4matlab/
6. Use anova to compare the goodness-of-fit of a SSfpl nls fit with a
linear model of your choice. How can your characterize the
degree-of-freedom-adjusted goodness of fit of nonlinear models?
I believe pairwise anova.nls is the optimal comparison for nonlinear
models, but there are several good choices for approximations,
including the residual standard error, which I believe can be adjusted
for degrees of freedom, as can the F statistic which TableCurve uses;
On Sun, Mar 7, 2010 at 7:35 PM, Chidambaram Annamalai
<quantumelixir at gmail.com> wrote:
> It's been a while since I proposed syrfr and I have been constantly in
> contact with the many people in the R community and I wasn't able to find a
> mentor for the project. I later got interested in the Automatic
> Differentiation proposal (adinr) and, on consulting with a few others within
> the R community, I mailed John Nash (who proposed adinr in the first place)
> if he'd be willing to take me up on the project. I got a positive reply only
> a few hours ago and it was my mistake to have not removed the syrfr proposal
> in time from the wiki, as being listed under proposals looking for mentors.
> While I appreciate your interest in the syrfr proposal I am afraid my
> allegiances have shifted towards the adinr proposal, as I got convinced that
> it might interest a larger group of people and it has wider scope in
> I apologize for having caused this trouble.
> Best Regards,
> On Mon, Mar 8, 2010 at 6:41 AM, James Salsman <jsalsman at talknicer.com>
>> Per http://rwiki.sciviews.org/doku.php?id=developers:projects:gsoc2010
>> -- and
>> -- I am applying to mentor the "Symbolic Regression for R" (syrfr)
>> package for the Google Summer of Code 2010.
>> I propose the following test which an applicant would have to pass in
>> order to qualify for the topic:
>> 1. Describe each of the following terms as they relate to statistical
>> regression: categorical, periodic, modular, continuous, bimodal,
>> log-normal, logistic, Gompertz, and nonlinear.
>> 2. Explain which parts of http://bit.ly/tablecurve were adopted in
>> SigmaPlot and which weren't.
>> 3. Use the 'outliers' package to improve a regression fit maintaining
>> the correct extrapolation confidence intervals as are between those
>> with and without outlier exclusions in proportion to the confidence
>> that the outliers were reasonably excluded. (Show your R transcript.)
>> 4. Explain the relationship between degrees of freedom and correlated
>> independent variables.
>> Best regards,
>> James Salsman
>> jsalsman at talknicer.com
>> R-devel at r-project.org mailing list
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