search for: simpleloess

...ell. 1 25: at -0.02 26: radius 0.0004 27: all data on boundary of neighborhood. make span bigger 28: pseudoinverse used at -0.02 29: neighborhood radius 0.02 30: reciprocal condition number nan 31: zero-width neighborhood. make span bigger 32: There are other near singularities as well. 1 33: In simpleLoess(y, x, w, span, degree, FALSE, FALSE, normalize = FALSE, ... : at -0.02 34: In simpleLoess(y, x, w, span, degree, FALSE, FALSE, normalize = FALSE, ... : radius 0.0004 35: In simpleLoess(y, x, w, span, degree, FALSE, FALSE, normalize = FALSE, ... : all data on boundary of neighborhood. mak...

...w loess package, regardless of whether package:loess or package:lattice comes first in the search list. If I export panel.loess from the new package, then it can't see grid.lines anymore. I've tried using fixInNamespace to change the loess.smooth in package:stats to point to the updated simpleLoess, but it is locked. At http://tolstoy.newcastle.edu.au/R/help/04/05/0428.html it was suggested to write a new panel function. However I still need to be able to access grid.lines, and getFromNamespace("grid.lines","grid") is not the way to do this. Any ideas? This seems simp...

...e randomly placed. Taking the first group as reference, there are thus 19 unknown offsets. The below code for toy data (spatial trend in one dimension x) works for two or three offset groups. Unfortunately, the loess call fails for four or more offset groups with the error message "Error in simpleLoess(y, x, w, span, degree, parametric, drop.square, normalize,? : ? only 1-4 predictors are allowed" See comment #1 I tried overriding the restriction (see lower section of code example) and got "k>d2MAX in ehg136.? Need to recompile with increased dimensions." How easy would that b...

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 control$iterations. I found also remarkable differences when comparing loess with PROC LOESS (in SAS) using...

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:

...base I checked the R FAQ, R for Windows FAQ, and the README associated with the Atlas BLAS on CRAN and couldn't find any information related to possible crash causes. I've used the ATLAS BLAS for about 6 months on this machine (it's a new machine) with R 2.6.2. Using debug(stats:::simpleLoess), I've found that the crash occurs on the first iteration of the line: z <- .C(R_loess_raw, as.double(y), as.double(x), as.double(weights), as.double(robust), as.integer(D), as.integer(N), as.double(span), as.integer(degree), as.integer(non...

...> > ### ** Examples > > require(graphics) > > with(cars, scatter.smooth(speed, dist)) Error in .Fortran(R_lowesw, as.double(fitted.residuals), as.integer(N), : Incorrect number of arguments (4), expecting 7 for lowesw Calls: with ... scatter.smooth -> loess.smooth -> simpleLoess -> .Fortran Execution halted This is on Fedora 8. Plots on the new X11() device look very nice though! Cheers, G -- %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% Dr. Gavin Simpson [t] +44 (0)20 7679 0522 ECRC, UCL Geography, [f] +44 (0)20 7679...

...y data (spatial trend in one dimension x) works for two or three offset groups, although I have not yet found out how to extract the fitted values for the globally fit parameters (the offsets). Unfortunately, the loess call fails for four or more offset groups with the error message "Error in simpleLoess(y, x, w, span, degree, parametric, drop.square, normalize, : only 1-4 predictors are allowed" Does anyone know of an implementation of local regression with global (parametric) offset groups that could be applied here, or is there a better way of dealing with this? Any comments would be g...

...d), data=tolerance.pp) ## this produces an error message xyplot(tolerance~age | factor(id), data=tolerance.pp, prepanel = function(x, y) prepanel.loess(x, y), panel = function(x, y){ panel.xyplot(x, y) panel.loess(x, y) }, ylim=c(0, 4), as.table=T) Error message is: >Error in simpleLoess(y, x, w, span, degree, FALSE, FALSE, normalize = FALSE, : > NA/NaN/Inf in foreign function call (arg 1) >In addition: There were 16 warnings (use warnings() to see them) [[alternative HTML version deleted]]

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 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

...controls in the maControls structure of marrayLayout as a vector of 0 and 1. Is someone still use it ? for the moment I just have ... test <- maNormMain(manip.raw, f.loc = list(maNormLoess(x="maA", y="maM", z="maControls",subset=TRUE))) but answer is Error in simpleLoess(y, x, w, span, degree, parametric, drop.square, normalize, : invalid `x' [[alternative HTML version deleted]]

...* Added new test file for wtd.mean, wtd.quantile * New test aregImpute3.r for glm Poisson regression * Improved describe.vector to format single unique values * Took aware warning about var, s.e., t, p in fit.mult.impute * Changed wtd.loess.noiter to use loess instead of stats:::simpleLoess -- Frank E Harrell Jr Professor and Chairman School of Medicine Department of Biostatistics Vanderbilt University _______________________________________________ R-packages mailing list R-packages at r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages

...R, the >> platform .... >> >>> It can be debugged in the following way: >> >> (Not in any sense of `debugged' that my dictionary mentions.) >> >>> 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 control$iterations. >> >> Why? The code contai...

Hi all, I am doing a projection pursuit regression using the ppr() function from modreg. I would also like to use predict.ppr(). However, I cannot find any information about it in the help files. There is a link to predict.ppr in the index for modreg, but that link is to the help for ppr(). Has predict.ppr() not been implemented? If not, does anyone have a suggestion as to how to implement

...re randomly placed. Taking the first group as reference, there are thus 19 unknown offsets. The below code for toy data (spatial trend in one dimension x) works for two or three offset groups. Unfortunately, the loess call fails for four or more offset groups with the error message "Error in simpleLoess(y, x, w, span, degree, parametric, drop.square, normalize,? : ? only 1-4 predictors are allowed" I tried overriding the restriction and got "k>d2MAX in ehg136.? Need to recompile with increased dimensions." How easy would that be to do? I cannot find a definition of d2MAX anywhe...