similar to: User Error (was LOESS (PR#9064))

Hello, I found a little BUG in loess <stats>. It does not receive the iterations parameter. It can be debugged in the following way: THIS IS AN EXCERPT FROM THE CODE: .... fit <- simpleLoess(y, x, w, span, degree, parametric, drop.square, normalize, control$statistics, control$surface, control$cell, iterations, control$trace.hat) Replace argument iterations with

Dear R developers! Considering I got no response or comments in the general r-help forum so far, perhaps my question is actually better suited for this list? I have added some more hopefully relevant technical details to my original post (edited below). Any comments gratefully received! Best regards, David Kreil. ---------- Dear R experts, I have a problem that is a related to the question

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

Hi there, I would like to draw a scatter plot and fit a smooth line by loess. Below is the data. However, the curve line started from 0, which my "resid" list doesn't consist of 0 value. It returned some warnings which I don't know if this is the reason affecting such problem. Here I also attached the warning messages. Please let me know if there is a solution to fix this. Thank

Is there an R implementation of a scheme for automatic smoothing parameter selection with loess, e.g., by minimizing one of the AIC/GCV statistics discussed by Hurvich, Simonoff & Tsai (1998)? Below is a function that calculates the relevant values of AICC, AICC1 and GCV--- I think, because I to guess from the names of the components returned in a loess object. I guess I could use

Dear R experts, I have a problem that is a related to the question raised in this earlier post https://stat.ethz.ch/pipermail/r-help/2007-January/124064.html My situation is different in that I have only 2 predictors (coordinates x,y) for local regression but a number of global ("parametric") offsets that I need to consider. Essentially, I have a spatial distortion overlaid over a

Dear R experts, I have a problem that is a related to the question raised in this earlier post ??? https://stat.ethz.ch/pipermail/r-help/2007-January/124064.html My situation is different in that I have only 2 predictors (coordinates x,y) for local regression but a number of global ("parametric") offsets that I need to consider. Essentially, I have a spatial distortion overlaid over a

There are two separate problems with loess under Guido's rw0632 on Windows, neither of which appear unless you try to do something that it is trying to tell you is inadvisable. It bombs trying to tell you. I have put up a replacement modreg.zip in the CRAN contrib collection that will be mirrored tonight. Both of these could potentially affect other platforms. (1) A problem relating to the

Dear List, Having had my appetite sufficiently whetted by Prof. Ripley's email about the new graphics capabilities in Unixes, I wanted to try them out. I updated to svn r44608, configured with the following options: R is now configured for x86_64-unknown-linux-gnu Source directory: .. Installation directory: /usr/local C compiler: gcc -O3 -g -std=gnu99

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 all, I was unable to obtained a smoothed line using the loess function. I used the following code reported in the examples of R documentation: cars.lo <- loess(dist ~ speed, cars) Then I tried to plot both the data and the smoothed line plot(cars) lines(cars.lo) but what I obtained is simply a broken line joining all the data points. I tried with different spans, but the results did not

Hi I am trying to get the tricube weights from the loess outputs as I need to calculate an error function which requires the weight. So I have used the following example from the R: cars.lo <- loess(dist ~ speed, cars, span=0.5, degree=1, family="symmetric") Then i try to get the weights: cars.lo$weights [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

Hi, I am segfaulting when using predict.loess() (checked with r62092). I've traced the source with the help of valgrind (output pasted below) and it appears that this is due to int overflow when allocating an int work array in loess_workspace(): liv = 50 + ((int)pow((double)2, (double)D) + 4) * nvmax + 2 * N; where liv is an (global) int. For D=1 (one x variable), this overflows at

I've created an xyplot that I want to add a trend line to using a subset of the data. The xyplot is xyplot(X9444500~WY,data=mynewdata,xlim=c(1900,2020),ylab="TEST", xlab="",ylim=c(100,100000),scales=list(x=list(at=c(1900,1920,1940,1960,1980,2000,2020),axs="r",tck=-1),y=list(log=TRUE,tck=-100,at=c(100,1000,10000,100000))), panel=function(x,y,...) {

Hi all, I am just learning R and I am trying to work through the book "Applied Longitudinal Data Analysis" by Singer & Willett. I have some code for this book that supposedly works in S-Plus (I don't have S-Plus so I can't verify that) and I am trying to run the examples in R. Most of the examples run, but I have one plot that gives me an error message. I have

hi! i want to change the "robustness weights" used by loess. these are described on page 316 of chambers and hastie's "statistical models in S" book as r_i = B(e_i,6m) where B is tukey's biweight function, e_i are the residulas, and m is the median average distance from 0 of the residuals. i want to change 6m to, say, 3m. is there a way to do this? i cant

I now have versions of code that is destined (I believe) for 0.63 which is in a suitable state for comment. The files are at ftp://ftp.stats.ox.ac.uk/pub/R (Our www server is being moved, so may be intermittently down, but this ftp server should be stable.) All are R packages, for the moment for personal use only (no re-distribution). Use with 0.62.3 or 0.63 (although I am aware of some

I have a question about running an optimization function on an existing LOESS function defined in R. I have a very large dataset (1 million observations) and have run a LOESS regression. Now, I want to run a Newton-Raphson optimization to determine the point at which the slope change is the greatest. I am relatively new to R and have tried several permutations of the maxNR and nlm functions with

Hi there fellow R-users, I have just upgraded to R version 1.9.0 from R version 1.7.1 for Windows. Im trying to use the loess smoother where the X-variable is an as.POSIXct variable. The following works fine with R1.7.1 but not with R1.9.0. Here is the example: dates<-c('2003-08-03','2003-08-10','2003-08-17','2003-08-24','2003-08-31','2