Since you have only one dependent variable, try using lowess() instead. It is less flexible -- only does local linear robust fitting -- but has arguments built in that allow you to sample and interpolate and limit the number of robustness iterations. It runs considerably faster as a result.
-- Bert On Fri, Apr 13, 2012 at 6:32 AM, Liaw, Andy <andy_l...@merck.com> wrote: > Alternatively, use only a subset to run loess(), either a random sample or > something like every other k-th (sorted) data value, or the quantiles. It's > hard for me to imagine that that many data points are going to improve your > model much at all (unless you use tiny span). > > Andy > > > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On > Behalf Of Uwe Ligges > > On 12.04.2012 05:49, arunkumar1111 wrote: >> Hi >> >> The function loess takes very long time if the dataset is very huge >> I have around 1000000 records >> and used only one independent variable. still it takes very long time >> >> Any suggestion to reduce the time > > > Use another method that is computationally less expensive for that many > observations. > > Uwe Ligges > > >> ----- >> Thanks in Advance >> Arun >> -- >> View this message in context: >> http://r.789695.n4.nabble.com/loess-function-take-tp4550896p4550896.html >> Sent from the R help mailing list archive at Nabble.com. >> >> ______________________________________________ >> R-help@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@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. > Notice: This e-mail message, together with any attachme...{{dropped:11}} > > ______________________________________________ > R-help@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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm ______________________________________________ R-help@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.