similar to: future update to loess

Full_Name: Benjamin Tyner Version: 2.1.0, 4/18/2005 OS: i686-redhat-linux-gnu Submission from: (NULL) (4.64.8.220) # Just run my.test() below in a newly opened R session. Once too many models have been fit (~20 on my system), the computed standard error jumps to a different value. This is (superficially) due to a different residual sum of squares, not a different one.delta. No other aspect of

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

Hi, I'm not sure what the recommended thing to do here would be: In the lattice library, panel.loess needs to use loess.smooth(), which is in the modreg library. Now should I (1) make lattice depend on modreg, and call require(modreg) in zzz.R OR (2) use autoload("loess", "modreg") I like the second option better, as a particular session might not need panel.loess.

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

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 Anupam Tyagi, You didn't include your data, so it's not possible to see exactly what happened, but I think that you misunderstand the object that loess() returns. It returns a "loess" object with several components, including the original data in x and y. So if pass the object to lines(), you'll simply connect the points, and if x isn't sorted, the points

Thanks, John. However, loess.smooth() is producing a very different curve compared to the one that results from applying predict() on a loess(). I am guessing they are using different defaults. Correct? On Thu, 23 Mar 2023 at 20:20, John Fox <jfox at mcmaster.ca> wrote: > Dear Anupam Tyagi, > > You didn't include your data, so it's not possible to see exactly what >

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]]

I'm updating the loess routines to allow for, among other things, arbitrary local polynomial degree and number of predictors. For now, I've given the updated package its own namespace. The trouble is, panel.loess still calls the original code in package:stats instead of the new loess package, regardless of whether package:loess or package:lattice comes first in the search list. If I

For some reason the following code is not plotting as I want it to. I want to plot a "loess" line plotted over a scatter plot. I get a jumble, with lines connecting all the points. I had a similar problem with "lowess". I solved that by dropping "NA" rows from the data columns. Please help. library(stats) attach(gini_pci_wdi_narm) plot(ny_gnp_pcap_pp_kd, si_pov_gini)

Hi, I am trying to create a loess smooth from hydrologic data. My goal is to create a smooth line that describes discharge at a certain point in time. I have done this using the 'lowess' function and had no problem, but I'm having some difficulty with loess. I am inputting the date ('date') and discharge ('q') values using the 'scan' function, then inputting

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

One more question... I need to use the Loess() function in the package modreg. What is the argument "formula" meant to be? A -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the

Hi, I am using Loess.smooth (Modreg) in order to infer certain relationship for the data set of ~130,000 observations with ~300 distinct values of single predictor. I understand that fitted values (y-hat) are just 300 Weighted LS fits in certain neighborhood of predictors. I am bit confused about how exactly is this neighborhood assigned . Say I choose spanning parameter = .5, for each LS

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]]

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

I was trying to plot some data in R. I used the following code to draw a loess fit and got the output as >?lines(lowess(log(abs(t(res))), log(abs(t(synthesised)))), col="red") Error in lowess(log(abs(t(res))), log(abs(t(synthesised)))) :?? NA/NaN/Inf in foreign function call (arg 1) Then I thought to use your Limma package for background correction. Do you think it's a right

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)

I like the functionality provided by outer=TRUE, but when it comes time to place separate xlabs or ylabs, I always end up 'eyeballing' it on a case-by-case basis. For example, ##begin example require(lattice) cars.lo <- loess(dist ~ speed, cars) print(xyplot(cars.lo$residuals+cars.lo$fitted~cars.lo$x, strip=FALSE, outer=TRUE, layout=c(1,2),