similar to: lowess regression

Hi, I have a scatter plot of the variables GNI and Lifeexp (Gross National Income and Life Expectancy, both metric). So I plotted them and I want to add a regression line and a lowess line. I use lowess and not loess because I have missing values. My code: plot(GNI,Lifeexp) abline(lm(Lifeexp~GNI), col="red") y.loess<-loess(Lifeexp~GNI,na. action = na.exclude)

code: x <- rnorm(32) y <- rnorm(32) plot(x,y) lines(lowess(x,y),col='red') Now I need to sample the lowess function into matrix where one series will be X and other will be values of lowess at particular X. -- View this message in context: http://r.789695.n4.nabble.com/how-to-sample-lowess-loess-into-matrix-tp3053458p3053458.html Sent from the R help mailing list archive at

Hi Every Body, I don't know why some regression functions have no related prediction function. For example lowess, loess, lokerns, lpridge, lpepa, and ksmooth. What could help? Is there any global or wrapper function so that can help? Regards, Amir Safari --------------------------------- [[alternative HTML version deleted]]

Hi, all, I want to use lowess(x, y) where x and y are vectors of length of 4000+. In fact, x and y are log of some vectors. So, some of the elements are NaN. lowess() can not take away those elements then do the fitting. It will give the error message and do nothing. 1. Can anybody tell me how to get rid of those NaN's and use lowess()? 2. How to get the LOWESS fitting values for any

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

As I've mentioned a number of times. I find it very useful to have lowess() become a generic function so that a lowess.formula() can be defined. Below is a patch that makes both changes, as well as updating the corresponding help documentation. Gregory R. Warnes Manager, Non-Clinical Statistics Pfizer Global Research and Development Tel: 860-715-3536 ? DESCRIPTION ? Makefile ?

Colleagues ---------------------------------- System info: R version rw1022 on NT ESS v. 5.1.18 using emacs ver. 20.4 ---------------------------------- I would like to access the residuals from a lowess fit (function lowess() ) as an aid to assessing whether I am over-smoothing or under-smoothing a dataset (as in Cleveland's book "Visualizing data", section 3.3) Unless I

Dear all, I'm trying to construct confidence intervals for a LOWESS estimation (by not using bootstrapping). I have checked previous posts and other material online and I understand that the main procedure is: my.count<- seq(...) fit<- loess (y ~ x, data=z) pred<- pred(fit, my.count, se=TRUE) and then the plotting. However, it's not working; as confidence

Hi there, Just out of curious, is there any difference between loess() and lowess() in R (and Splus in fact). Which one is more often used? Thanks, Ko-Kang Wang ------------------------------------------------------------------------------ Ko-Kang Kevin Wang Statistical Analysis Division Leader Software Developers' Klub (SDK) University of Auckland New Zealand

Hi folks. If I have the following in my "data" event pH1 pH2 1 4.0 6.0 2 4.3 5.9 3 4.1 6.1 4 4.0 5.9 and on and on..... for about 400 events Is there a way I can get R to plot event vs. pH1 and event vs. pH2 and then do a loess or lowess line for each?? Thanks in advance David [[alternative HTML version deleted]]

Hi there, I'm plotting some glass RI values just by plotting plot(x) then I put on my lowess smoother lines(lowess(x)) now I want to put on some 95% Confidence Interval bands of the lowess smoother, but don't know how?? Thanks -- Gareth Campbell PhD Candidate The University of Auckland P +649 815 3670 M +6421 256 3511 E gareth.campbell@esr.cri.nz gcam032@gmail.com [[alternative

Dear Masters, I'm driving crazy with the lowess() function.... my intent is smoothing confidence intervals for predicted y values in a linear model lm() setting since in the predict() function there exists an option for predicting NA values, I instead encounter problems when I fit a missing values x variable to the predicted terms.....,impossible task!!! I've been banging on my head

Hi there, I cant seem to find a way for the lowess smoothing function to handle "NA" values. Can anyone help?? Regards, Wayne Dr Wayne R. Jones Statistician / Research Analyst KSS Group plc St James''s Buildings 79 Oxford Street Manchester M1 6SS Tel: +44(0)161 609 4084 Mob: +44(0)7810 523 713 KSS Ltd A division of Knowledge Support Systems Group plc Seventh Floor St

I'm using this code to plot a smoothed line. These two columns of data really represent 4 groups and I'd like to plot a separate line for each group but have them all in the same plot. The R-Docs for lowess do not seem to indicate some type of "GROUPS=var_name" option. What would be the syntax for this? plot(AWGT ~ lipid ) lines(lowess(lipid , AWGT, f=.8)) -- Dean

Hi All, I've been providing a generic version of lowess() in my 'gregmisc' library, along with a 'lowess.formula' and 'lowess.default'. Can/should these be moved into base? -Greg LEGAL NOTICE Unless expressly stated otherwise, this message is confidential and may be privileged. It is intended for the addressee(s) only. Access to this E-mail by anyone else

I am trying to change the attributes of the lowess lines fit to an xyplot command, but have been unsuccessful in my search of the online help. Right now, both the points and lowess line come out in the same color (blue). I am unsure how I can change the properties of the lowess line separately. xyplot ( SnowLineElevation ~ Year | Model, data = data, ylim = c(0,1800), type =

Dear all, To draw a lowess line on a plot was a piece of cake; to draw a loess line, however, seems not that easy. Is the loess plotting implemented at all in relation to the loess function, or do I have to look in add-on packages? Thanks, Marcin

Dear R-community, maybe someone can help me with this: I've been using the loess() smoother for quite a while now, and for the matter of documentation I'd like to resolve the acronym LOESS. Unfortunately there's no explanation in the help file, and I didn't get anything convincing from google either. I know that the predecessor LOWESS stands for "Locally Weighted

Hi Bogdan, Kinda messy, but: N <- data.frame(N=c("n1","n2","n3","n4")) M <- data.frame(M=c("m1","m2","m3","m4","m5")) C <- data.frame(n=c("n1","n2","n3"), m=c("m1","m1","m3"), I=c(100,300,400))

I wonder if someone can give some pointers on alternatives to linear regression (e.g. Loess) when dealing with multiple variables. Taking any simple table with three variables, you can very easily get the intercept and coefficients with: summary(lm(read_table)) For obvious reasons, the coefficients in a multiple regression are quite different from what you get if you calculate regressions for