similar to: Loess with more than 4 predictors / offsets

This is a general question to people who've installed R on a UNIX sparc-sun-solaris platform: Have you had any issues related to maintaining R on this platform, e.g., installations that didn't work, instances of R crashing and possibly requiring a new installation, etc? I'm especially interested in anyone who has experience with both R and S-Plus on this OS. Is there any reason to

Hi, I'm working on a server with a sparcv9 chip using SunOS 5.9 Generic May 2002. The compilers are the Sun Studio 12 compilers. I'm trying to build a 64-bit version of R-2.6.1, and while the configure script runs, the make does not. Here are the options I set in config.site: ________________________________________________________________________ _ R_PAPERSIZE=letter CC="cc

Hello, I am interested in performing a 2D loess smooth on microarray data, i.e. log2 ratios on a 2D grid, using different spans in the horizontal and vertical directions (the immediate reason being that replicate spots are laid out in the horizontal direction). Is it possible to do this in R? Functions like loess(stats) seem to apply the same span for all predictors, which carries over to

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

Hi, I have a UNIX-Solaris-Sparc-Studio 11 compilers question. Since it's not exactly a programming question, I'm posting it here instead of to the developers list. Here's the relevant info: 1) I'm using SunOS 5.9 on a 32 bit machine without parallel processing. The chip is Sparc. 2) I've installed the Sun Studio 11 compilers. 3) I've successfully built and tested R 2.5.1

Hi, I believe my question is pretty simple, but I'd like to give you brief background first: I work at a company with UNIX installed on a sparc-sun-solaris platform; the OS version is SunOS 5.9. Several of us who work here have been advocating for the installation of R on this server. The IT security group at my company prefers not to install the gcc compilers on our UNIX production servers;

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

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

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

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 have a data frame with 6563 observations. I can run a regression with loess using four explanatory variables. If I add a fifth, R crashes. There are no missings in the data, and if I run a regression with any four of the five explanatory variables, it works. Its only when I go from four to five that it crashes. This leads me to believe that it is not an obvious problem with the data,

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

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)

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

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

If a run a LOESS model and then produce a smoothed surface: Is there any way to determine the coordinates of the local maxima on the surface? [[alternative HTML version deleted]]

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