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From: Maggie Xiong <maggiexyz@us...>  20110428 01:39:02

Thank you David. I'll add it to the todo list for the next release. Best, Maggie On Wed, Apr 27, 2011 at 8:35 AM, <dwm042@...> wrote: > > Thank you Maggie. > > What I'd like to be able to do, with things like the logistic function > (any curve fitter > in PDL::Stats, actually) is something like this: > > my %m = $y>logistic( COV => 1 ); > print $m{cov}>corr_table(); > > I don't think logistic should return the covariance matrix by default, > but I would like > to be able to get to it. > > A single line patch in GLM.pm, after %ret is declared, around line 2000 > or so.. > > $ret{cov} = $cov if ( $opt{COV} ); > > would do the trick for logistic, I believe. I don't think $cov is out of > scope by that point. > > Sincerely, > > David Myers. > > > > >  > WhatsUp Gold  Download Free Network Management Software > The most intuitive, comprehensive, and costeffective network > management toolset available today. Delivers lowest initial > acquisition cost and overall TCO of any competing solution. > http://p.sf.net/sfu/whatsupgoldsd > _______________________________________________ > pdlstatshelp mailing list > pdlstatshelp@... > https://lists.sourceforge.net/lists/listinfo/pdlstatshelp > > 
From: <dwm042@em...>  20110427 12:53:06

Thank you Maggie. What I'd like to be able to do, with things like the logistic function (any curve fitter in PDL::Stats, actually) is something like this: my %m = $y>logistic( COV => 1 ); print $m{cov}>corr_table(); I don't think logistic should return the covariance matrix by default, but I would like to be able to get to it. A single line patch in GLM.pm, after %ret is declared, around line 2000 or so.. $ret{cov} = $cov if ( $opt{COV} ); would do the trick for logistic, I believe. I don't think $cov is out of scope by that point. Sincerely, David Myers. 
From: Maggie Xiong <maggiexyz@us...>  20110426 13:00:32

In the context of logistic regression, by cross correlation you mean Pearson correlation matrix for a set of variables? The function corr_table() in PDL::Stats::Basic can give you that. You can also calculate it from covariance matrix by dividing the covariance with the product of of the standard deviations of the two variables you are correlating with. Best, Maggie On Mon, Apr 25, 2011 at 10:54 PM, <dwm042@...> wrote: > > I apologize in advance if this is obvious. I'm an exscientist, from a > generation for which Bevington's "Data Reduction > and Error Analysis in the Physical Sciences" was our Bible. To determine > cross correlation of a fit, we'd extract > the covariance matrix from our fitters, do some math presto magico things, > and then could determine if > we were fitting cross correlated data (then drop one of the correlated > coefficients from our models..). > > I'm working with PDL::Stats logistic method. Works great, but haven't a > clue how to detect cross correlation. > I suspect the "how" is obvious to a stats major, but not to an > exbiochemist like me. The underlying fitter > returns $cov, but no clue how to get to it. > > Any help appreciated. > > Sincerely, > > David Myers. > > >  > WhatsUp Gold  Download Free Network Management Software > The most intuitive, comprehensive, and costeffective network > management toolset available today. Delivers lowest initial > acquisition cost and overall TCO of any competing solution. > http://p.sf.net/sfu/whatsupgoldsd > _______________________________________________ > pdlstatshelp mailing list > pdlstatshelp@... > https://lists.sourceforge.net/lists/listinfo/pdlstatshelp > > 
From: <dwm042@em...>  20110426 03:10:01

I apologize in advance if this is obvious. I'm an exscientist, from a generation for which Bevington's "Data Reduction and Error Analysis in the Physical Sciences" was our Bible. To determine cross correlation of a fit, we'd extract the covariance matrix from our fitters, do some math presto magico things, and then could determine if we were fitting cross correlated data (then drop one of the correlated coefficients from our models..). I'm working with PDL::Stats logistic method. Works great, but haven't a clue how to detect cross correlation. I suspect the "how" is obvious to a stats major, but not to an exbiochemist like me. The underlying fitter returns $cov, but no clue how to get to it. Any help appreciated. Sincerely, David Myers. 