Thanks. Should have noticed this myself. Dale Smith, Ph.D. Senior Financial Quantitative Analyst Risk & Compliance Fiserv Office: 678-375-5315 www.fiserv.com
-----Original Message----- From: Hadley Wickham [mailto:[email protected]] Sent: Thursday, March 21, 2013 11:55 AM To: Smith, Dale Cc: [email protected] Subject: Re: [Rcpp-devel] [rcpp-devel] Rcpp Gallery Example fastLm vs R native lm On Thu, Mar 21, 2013 at 10:44 AM, Smith, Dale <[email protected]> wrote: > I have a question about the fastLm example in the Gallery > http://gallery.rcpp.org/articles/fast-linear-model-with-armadillo/. I > put the code directly into my package (after renaming it fastLmProto > so I don't mask the RcppArmadillo function by the same name). After > building the package, I wanted to compare results: > > > >> require(datasets) > >> coef(lm(y1 ~ x1, data = anscombe)) > > (Intercept) x1 > > 3.0000909 0.5000909 > >> coef(fastLmProto(anscombe$y1, as.matrix(anscombe$x1))) > > [,1] > > [1,] 0.7968032 > >> coef(fastLm(anscombe$y1, as.matrix(anscombe$x1))) > > [1] 1.208169 > > > > Should I expect the results to match? Why do fastLmProto and fastLm > produce a single fitted parameter (I would expect two)? Why are they > different? Am I doing something wrong here, or just being naïve in my > assumptions? Hint: > coef(lm(y1 ~ x1 - 1, data = anscombe)) x1 0.7968032 Hadley -- Chief Scientist, RStudio http://had.co.nz/ _______________________________________________ Rcpp-devel mailing list [email protected] https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
