From: David Winsemius <dwinsemius_at_comcast.net>

Date: Fri, 18 Jun 2010 21:31:54 -0400

Date: Fri, 18 Jun 2010 21:31:54 -0400

On Jun 18, 2010, at 7:54 PM, David Jarvis wrote:

*> Hi,
**>
*

> Standard correlations (Pearson's, Spearman's, Kendall's Tau) do not

*> accurately reflect how closely the model (GAM) fits the data. I was
**> told
**> that the accuracy of the correlation can be improved using a root mean
**> square deviation (RMSD) calculation on binned data.
*

By whom? ... and with what theoretical basis?

*>
*

> For example, let 'o' be the real, observed data and 'm' be the model

*> data. I
**> believe I can calculate the root mean squared deviation as:
**>
**> sqrt( mean( o - m ) ^ 2 )
**>
**> However, this does not bin the data into mean sets. What I would
**> like to do
**> is:
**>
**> oangry <- c( mean(o[1:5]), mean(o[6:10]), ... )
**> mangry <- c( mean(m[1:5]), mean(m[6:10]), ... )
**>
**> Then:
**>
**> sqrt( mean( oangry - mangry ) ^ 2 )
**>
**> That calculation I would like to simplify into (or similar to):
**>
**> sqrt( mean( bin( o, 5 ) - bin( m, 5 ) ) ^ 2 )
*

I doubt that your strategy offers any statistical advantage, but if you want to play around with it then consider:

binned.x <- round( (x + 2.5)/5)

-- David.Received on Sat 19 Jun 2010 - 01:35:28 GMT

>

> I have read the help for ?cut, ?table, ?hist, and ?split, but am

> stumped for> which one to use in this case--if any.>> How do you calculate c( mean(o[1:5]), mean(o[6:10]), ... ) for an> arbitrary> length vector using an appropriate number of bins (fixed at 5, or> perhaps> calculated using Sturges' formula)?>> I have also posted a more detailed version of this question on> StackOverflow:>> http://stackoverflow.com/questions/3073365/root-mean-square-deviation-on-binned-gam-results-using-r>> Many thanks.>> Dave>> [[alternative HTML version deleted]]>> ______________________________________________> R-help_at_r-project.org mailing list> https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.

______________________________________________ R-help_at_r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.

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