On Wed, 2010-10-27 at 08:26 +0100, Gavin Simpson wrote: > On Tue, 2010-10-26 at 13:29 -0700, Peter Ehlers wrote: > > On 2010-10-26 11:48, Jonathan P Daily wrote: > > > ?loess > > > > > > use this instead: > > If you change this: > > > > fit<- loess(b~a) > > to be this: > > fit <- loess(b~a, na.action = na.exclude) > > then this: > > > > lines(a, predict(fit)) > > will work.
I meant "will work in general". In this particular case, the data are not ordered in 'a' so it still gives a cradle of lines. The above was meant to address the "incomplete cases" issue. G > G > > > I don't think that will work when there are incomplete cases, > > in which case 'a' and predict(fit) may not correspond. > > > > I think that it's always best to define a set of predictor > > values and use predict() to get the corresponding fits and > > plot according to taste: > > > > fm <- loess(b ~ a) > > aa <- seq(0, 1000, length=101) > > bb <- predict(fm, aa) > > lines(aa, bb, col="blue", lwd=2) > > > > @Federico: see further comments below. > > > > > -------------------------------------- > > > Jonathan P. Daily > > > Technician - USGS Leetown Science Center > > > 11649 Leetown Road > > > Kearneysville WV, 25430 > > > (304) 724-4480 > > > "Is the room still a room when its empty? Does the room, > > > the thing itself have purpose? Or do we, what's the word... imbue it." > > > - Jubal Early, Firefly > > > > > > > > > > > > From: > > > Federico Bonofiglio<bonori...@gmail.com> > > > To: > > > r-help@r-project.org > > > Date: > > > 10/26/2010 02:38 PM > > > Subject: > > > [R] anomalies with the loess() function > > > Sent by: > > > r-help-boun...@r-project.org > > > > > > > > > > > > Hello Masters, > > > > > > I run the loess() function to obtain local weighted regressions, given > > > lowess() can't handle NAs, but I don't > > > improve significantly my situation......, actually loess() performance > > > leave > > > me much puzzled.... > > > > > > I attach my easy experiment below > > > > > > #------SCRIPT---------------------------------------------- > > > > > > #I explore the functionalities of lowess()& loess() > > > #because I have encountered problems in execute local weighted regressions > > > #with lowess() (in presence of NAs)& with loess() (always!!!) > > > > > > > > > #I generate 2 fictious vectors > > > > > > a<-sample(c(sample(1:1000,100),rep(NA,50))) > > > > > > b<-sample(c(sample(1:1000,100),rep(NA,50))) > > > > > > #lm() has no problems..can handle the missing values > > > plot(a,b) > > > abline(lm(b~a),col="red",lwd=2) > > > > > > #loess return a plain mess like it would go dizzed with ordering or > > > something. > > > > Yes, the 'mess' is due to the unordered nature of your data. > > lines() will plot in the order in which the points occur in > > your data. You could order before calling loess: > > > > ord <- order(a) > > a1 <- a[ord] > > b1 <- b[ord] > > fm <- loess(b1 ~ a1) > > > > > #Off course lowess() turns useless in presence of NAs, I don't even try > > > it. > > > > > > lines(loess(b~a)) > > > > > > #I get rid off NAs and compare lowess()& loess() performance, expecting > > > to > > > #obtain the same result as both functions implement local weighted > > > regressions > > > > > > a<-na.omit(a) > > > b<-na.omit(b) > > > > This is a bad idea. The values of 'a' and 'b' will no longer > > be paired. Another reason to prefer dataframes. > > > > > > > > #check out the evidence.....something's wrong with loess()??? > > > > There's nothing wrong with loess; it just needs more than a > > single intercept and slope to plot its predictions. > > > > -Peter Ehlers > > > > > > > > par(mfrow=c(1,2)) > > > plot(a,b) > > > lines(lowess(a,b),col="red")#if NAs are excluded lowess() runs regularly > > > plot(a,b) > > > lines(loess(b~a),col="red")#.....but loess() keeps messing all > > > over...!!??? > > > > > > > ______________________________________________ > > 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. > > -- > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% > Dr. Gavin Simpson [t] +44 (0)20 7679 0522 > ECRC, UCL Geography, [f] +44 (0)20 7679 0565 > Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk > Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/ > UK. WC1E 6BT. [w] http://www.freshwaters.org.uk > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% > > ______________________________________________ > 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. -- %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% Dr. Gavin Simpson [t] +44 (0)20 7679 0522 ECRC, UCL Geography, [f] +44 (0)20 7679 0565 Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/ UK. WC1E 6BT. [w] http://www.freshwaters.org.uk %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% ______________________________________________ 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.
