similar to: $

hi, did'nt see anything in the archive: map('world',pro='rectangular',para=0) yields a strange artifact (horizontal bar) extending over the whole map at a certain latitude range (approx 65 deg. north), whereas map('world',pro='rectangular',para=180) (which should be the same) does not show the artifact. the artifact shows up in other projections as well,

Full_Name: joerg van den hoff Version: 1.9.0 and 1.7.1 OS: MacOS (1.9.0), SunOS (1.7.1) Submission from: (NULL) (149.220.4.88) something like (sure not the originally intended input, but something like this can happen...): approx(c(1,2),c(NA,NA),1.5) crashes R (bus error under MacOS, segmentation fault under SunOS). search of the bug archive did not work. I hope this bug was not reported

I have encountered the following problem: I need to extract from a list of lists equally named compenents who happen to be 'one row' data frames. a trivial example would be: a <- list(list( df = data.frame(A = 1, B = 2, C = 3)), list(df = data.frame(A = 4,B = 5,C = 6))) I want the extracted compenents to fill up a matrix or data frame row by row. the obvious thing to do seems: b

Full_Name: joerg van den hoff Version: 1.9.1 OS: MacOS and SunOS Submission from: (NULL) (149.220.4.88) follow up to ID 7166. something like approx(c(1,2),c(NA,NA),1.5,rule=2) crashes 1.9.1 on both systems (MacOS 10.3.5.: bus error, SunOS 5.9: segmentation fault) even if xout is within given x range (as in example above) where rule=2 seems not be relevant anyway.

I need to make plots similar to those produced by the s-plus rayplot function but can't seem to find it in R. These 'vector maps' plot a ray or vector at each specified location. Is there something similar in R ? --Rich Richard Kittler AMD TDG 408-749-4099

I recently coded a recursion algorithm in R and ir ran a few days without returning any result. So I decided to try a simple case of computing binomial coefficient using recusrive relationship choose(n,k) = choose(n-1, k)+choose(n-1,k-1) I implemented in R and Fortran 90 the same algorithm (code follows). The R code finishes 31 minutes and the Fortran 90 program finishes in 6 seconds. So the

I need to extract identically named columns from several data frames in a list. the column name is a variable (i.e. not known in advance). the whole thing occurs within a function body. I'd like to use lapply with a variable 'select' argument. example: tt <- function (n) { x <- list(data.frame(a=1,b=2), data.frame(a=3,b=4)) for (xx in x) print(subset(xx, select = n))

I raised this question quite some time ago but it quitly went down the river. I'll give it a second try (before keeping my modified version of matplot for ever...): matplot supports vectors (and/or character strings) for a number of arguments namely `type', `lty', `lwd', `pch', `col', `cex'. all of them act consistently in such a way that the first entries are used

hi list, used versions: 2.12.1 and 2.14.0 under ubuntu and macosx. I recently stumbled over a problem with `nls', which occurs if the model is not specified explicitly but via an evaluation of a 'call' object. simple example: 8<-------------------------------------------------------------------------------------- nlsProblem <- function (len = 5) {

hi everybody, I noticed the following: in one of my scripts 'layout' is used to generate a (approx. square) grid of variable dimensions (depending on no. of input files). if the no. of subplots (grid cells) becomes moderately large (say > 9) I use a construct like ###layout grid computation and set up occurs here### ... opar <- par(no.readonly = T);

I have a vector that has 1,974 elements and each element is one of the following (B, F, N, Y). How do I recreate that vector accept in the place of N put 0 and in the place of B, F or Y put a 1? Thanks, Jacob [[alternative HTML version deleted]]

In summary.glm I'm trying to get a better feel for the z output. The following lines can be found in the function 1 if (p > 0) { 2 p1 <- 1:p 3 Qr <- object$qr 4 coef.p <- object$coefficients[Qr$pivot[p1]] 5 covmat.unscaled <- chol2inv(Qr$qr[p1, p1, drop = FALSE]) 6 dimnames(covmat.unscaled) <- list(names(coef.p), names(coef.p))

Dear all, I would like to use the Levenberg-Marquardt algorithm for non-linear least-squares regression using function nls.lm. Can anybody help me to find a a way to compute confidence intervals on the fitted parameters as it is possible for nls (using confint.nls, which does not work for nls.lm)? Thank you for your help Michael

Hi I have been searching for goodness-of-fit tests (or lack of fit tests) for GAMs and cannot find anything. My problem is: after fitting a GAM to mortality data (smoothing crude estimated rates of mortality - a process called graduation in the actuarial literature), (1) how to assess the fit of the model with reference to "adherence to data" for the fitted model (I do not think the

I have recently fit a binomial link = logit model and I want to visually see the estimated response across a specific covariate. I can accomplish this by creating a function that extracts the betas from the model then forms a linear combination with the classes I'm interested in next pass the value through the inverse logit function, do this for each class in a covariate, then plot the

Good morning, Is there anyway to do Mixed Exponential Distribution in R? I am trying to load some lag-weighted empirical survival distribution into R and run a mixed exponential on that data. Thanks, Jacob Fazekas Jacob Fazekas Assistant Actuary Auto-Owners Insurance Company 517-703-2543 fazekas.jacob@aoins.com [[alternative HTML version deleted]]

Hi all, I am running a bivariate regression with the following: p1=c(184,155,676,67,922,22,76,24,39) p2=c(1845,1483,2287,367,1693,488,435,1782,745) I1=c(1530,1505,2505,204,2285,269,1271,298,2023) I2=c(8238,6247,6150,2748,4361,5549,2657,3533,5415) R1=I1-p1 R2=I2-p2 x1=cbind(p1,R1) y1=cbind(p2,R2) fit1=lm(y1~-1+x1) summary(fit1) Response 2: Coefficients: Estimate Std. Error t value

This is an initial implementation of HDMI 3D mode support for the nouveau kernel driver. It works on all of the hardware that I have available to test at the moment, but I am unsure as to the overall approach taken for setting HDMI InfoFrames, there's no support for g84 or gf119 disps, and the criteria for enabling stereo support for an output seems a bit iffy. The first four patches arrange

How does one implement a likelihood-ratio test, to test whether the variances of the random effects differ between two groups of subjects? Suppose your data consist of repeated measures on subjects belonging to two groups, say boys and girls, and you are fitting a linear mixed-effects model for the response as a function of time. The within-subject errors (residuals) have the same variance in

Hi, Which is the recommended filesystem to be used for the bricks in glusterFS. ?? XFS/EXT3/EXT4 etc .???? Thanks & Regards, Bobby Jacob Senior Technical Systems Engineer | eGroup P SAVE TREES. Please don't print this e-mail unless you really need to. -------------- next part -------------- An HTML attachment was scrubbed... URL: