[SciPy-User] Bootstrapping confidence interval of the maximum of a smoothing spline

Giovanni Luca Ciampaglia ciampagg@usi...
Mon Aug 22 16:48:29 CDT 2011

Hi all, I have data on editing activity from an online community and I 
am trying to estimate the day of peak activity using smoothing splines.

I determine the smoothing factor for scipy.interpolate.UnivariateSpline 
by leave-1-out crossvalidation, and then use scipy.optimize.fmin_tnc to 
evaluate the maximum from the resulting spline. This works pretty well 
and seems robust enough (e.g. http://tinypic.com/r/a3m739/7). Now I 
would like to compute the confidence intervals for this estimate, but I 
am not exactly sure on how to proceed, since I cannot sample data from 
my non-parametric model and generate a distribution for this estimator.

I was thinking at applying some noise to the smoothing factor, but I am 
not sure whether this approach has any theoretical basis. Any idea?


Giovanni Luca Ciampaglia

Ph.D. Candidate
Faculty of Informatics
University of Lugano
Web: http://www.inf.usi.ch/phd/ciampaglia/

Bertastraße 36 ∙ 8003 Zürich ∙ Switzerland

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