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.
