similar to: LOESS (PR#9064)

Please do as we ask (repeatedly) and study the help page before posting. 'family' is a separate argument, not part of loess.control, as the help page correctly documents. If you use cars.lo2 <- loess(dist ~ speed, cars, family = "symmetric", control = loess.control(surface = "direct", iterations = 20)) cars.lo2$pars$iterations it prints *20*, as it is

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

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 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

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

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

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 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

Respected R experts, I am trying to apply a user function that basically calls and applies the R loess function from stat package over each time series. I have a large matrix of size 21 X 9000000 and I need to apply the loess for each column and hence I have implemented this separate user function that applies loess over each column and I am calling this function foo as follows:

I noticed a problem using R 2.7.1 on Windows XP SP2 with the precompiled Atlas Rblas.dll. Running the code below causes R to crash. I started R using Rgui --vanilla and am using the precompiled Atlas Rblas.dll from cran.fhcrc.org dated 17-Jul-2007 05:04 for Core2 Duo. The code that causes the crash: x <- rnorm(100) y <- rnorm(100) z <- rnorm(100) loess(z ~ x * y) loess(z ~ x) does

Hi mailinglist members, I’m actually working on a time series prediction and my current approach is to decompose the series first into a trend, a seasonal component and a remainder. Therefore I’m using the stl() function. But I’m wondering how to get the single components in order to predict the particular fitted series’. This code snippet illustrates my problem: series <-

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

Greetings and happy new year! I am in the process of converting some of the old S-PLUS scripts from Visualizing Data (Cleveland, 1993) into lattice. In fact, I did most of it several years ago, and at the time, all of the scripts that contained loess() worked fine. Tonight, I ran most of the scripts again, but every one that I tried with a loess() call crashed R. I tried it in two sessions, one

Dear John, > I suggest that you look at the abilities of the mgcv package. > There are notes of mine at > > http://www.maths.anu.edu.au/%7Ejohnm/r-book/xtras/autosmooth.pdf > > that may help you get started. Thank?you very much for the suggestion and the link to your write-up, it was indeed very helpful! I have experimented with this library for a while now and am really happy

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 >

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

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

Dear R community, I am trying to understand how the predict function, specifically, the predict.loess function works. I understand that the loess function calculates regression parameters at each data point in 'data'. lo <- loess ( y~x, data) p <- predict (lo, newdata) I understand that the predict function predicts values for 'newdata' according to the loess regression

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