similar to: trouble locating confint function/ nls library/

"SM" == S McClatchie <S.McClatchie> writes: > > SM> I notice that the new option under R ver. 1.3.0 to save a > SM> graph as a pdf file from the graph window menu (file/ save as/ SM> > PDF) works differently (extremely slowly) under ESS, whereas SM> it is > almost instant from the R- gui. > > SM> Does the feature not work

Colleagues ---------------------------------- System info: R version rw1022 on NT ESS v. 5.1.18 using emacs ver. 20.4 ---------------------------------- I would like to access the residuals from a lowess fit (function lowess() ) as an aid to assessing whether I am over-smoothing or under-smoothing a dataset (as in Cleveland's book "Visualizing data", section 3.3) Unless I

Full_Name: Ben Bolker Version: 2.2.1 OS: Windows XP and 2000 Submission from: (NULL) (128.227.60.124) The following code, using confint() to try to get confidence intervals on an nls object that has been fitted with algorithm="port" reliably crashes R 2.2.0 and 2.2.1 with the latest version of MASS on a Windows 2000 and a Windows XP machine here. I *think* earlier versions of MASS

I have found some "issues" (bugs?) with nls confidence intervals ... some with the relatively new "port" algorithm, others more general (but possibly in the "well, don't do that" category). I have corresponded some with Prof. Ripley about them, but I thought I would just report how far I've gotten in case anyone else has thoughts. (I'm finding the code

Colleagues ---------------------------------- System info: Version 1.2.3 (2001-04-26) on NT ESS v. 5.1.18 using emacs ver. 20.4 ---------------------------------- I am wondering if there is a problem with the function rep(). Both the commands using rep() below were expected to produce 8 twos, but only the second did. x <- rep(2,40*(1-0.8)) length(x) y <- rep(2,40*0.2) length(y)

Colleagues ---------------------------------- System info: R version rw1022 on NT ESS v. 5.1.18 using emacs ver. 20.4 ---------------------------------- I notice that saving a file from the menu bar in the graph window to 100% quality jpeg is very slow (more than 2 minutes). Is this something to be avoided? I know I can save the graph with postscript() in the script, or cut and paste into

Colleagues ---------------------------------- System info: R version rw1022 on NT ESS v. 5.1.18 using emacs ver. 20.4 ---------------------------------- As recommended, I keep separate directories for projects, but also use separate sub-directories for types of data (e.g. different oceanographic instruments) within projects. My problem is that I often need to access the objects and data (not

Colleagues ---------------------------------- System info: R version rw1022 on NT ESS v. 5.1.18 using emacs ver. 20.4 ---------------------------------- I want to documnet a function I've written. I used prompt(function.name) to create an ascii R documentation file. I moved the .Rd file into a subdirectory called rw1022/library/my.functions/man Now I want to load the help using

The following sequence of commands (for example): >my.data<-rnorm(10000, 5, 1) >my.data fills my pager buffer beyond its capacity. When I type "my.data", the pager displays approximately the bottom 7000 cells of the file, but "loses" the first 3000. Is there a some setting that increases the size of the pager buffer, or is this a limit in the Windows version?

Colleagues ---------------------------------- System info: R version rw1022 on NT ESS v. 5.1.18 using emacs ver. 20.4 ---------------------------------- I have some rather unusual units for acoustic volume backscattering integrated over several metres depth and 10 transmits (which happens to = 160 m along transect). I need to express these units in a graph label. My problem

Colleagues ---------------------------------- System info: R version rw1020 on NT ESS using emacs ver. 20.4 ~/.emacs ; Default function template (setq ess-insert-function-templates t) ---------------------------------- When loading a new function into the R workspace using ctrl-CD I would like the default function template to come up, rather than a blank buffer. I thought I had the Default

I need confint() for glm() to supress the messages "Waiting for profiling to be done..." because they mess up the caching mechanism of pgfSweave (see https://github.com/cameronbracken/pgfSweave/issues/40). I have read the help page of confint(), but I do not know how to get the help page for the glm() version, if any such help page exists. Is there a general way of turning of output

Hi, I have a glm gives summary as follows, Estimate Std. Error z value Pr(>|z|) (Intercept) -2.03693352 1.449574526 -1.405194 0.159963578 A 0.01093048 0.006446256 1.695633 0.089955471 N 0.41060119 0.224860819 1.826024 0.067846690 S -0.20651005 0.067698863 -3.050421 0.002285206 then I use confint(k.glm)

System info: Linux slackware R Version 1.5.1 (2002-06-17) ESS 5.1.21 Emacs 21.2.1 ------------------- Colleagues Is there a way to add a legend to an image plot? I don't see any reference to legends in the documentation (so I suppose the answer is no?). Although the documentation says image takes plot() parameters, it isn't clear to me how the usual use of legend in a plot command

System info: Linux slackware R Version 1.5.1 (2002-06-17) ESS 5.1.21 Emacs 21.2.1 ------------------- Colleagues I have some text files in a certain directory and want to process them sequentially. So I want to pass the filename identifier into a function and loop through the processing of each file in turn.I've called the file identifier f in this code segment: image.dvm <- function

It seems that confint.default returns an empty data.frame for objects of class mlm. For example: ``` nobs <- 20 set.seed(1234) # some fake data datf <- data.frame(x1=rnorm(nobs),x2=runif(nobs),y1=rnorm(nobs),y2=rnorm(nobs)) fitm <- lm(cbind(y1,y2) ~ x1 + x2,data=datf) confint(fitm) # returns: 2.5 % 97.5 % ``` I have seen proposed workarounds on stackoverflow and elsewhere, but

I can't get confint.glm to work from within a function. Consider the following (using R 1.9.1, Windows 2000): # FIRST: SOMETHING THAT WORKS FROM A COMMAND PROMPT DF <- data.frame(y=.1, N=100) (fit <- glm(y~1, family=binomial, data=DF, weights=DF[,"N"])) Call: glm(formula = y ~ 1, family = binomial, data = DF, weights = DF[, "N"]) Coefficients:

System info: Red Hat 9.0 R Version 1.7.0 ESS 5.1.21 Emacs 21.2.1 ------------------- Colleagues At work I've had to migrate from Mandrake 9.1 to Red Hat 9.0 and I'm reinstalling R. I am having a problem downloading from R-1.7.1-1.i386.rpm from /bin/linux/redhat/9/i386. Basically the download does not complete. I am using mozilla, and when I click on the link the screen corrupts with

? Tue, 21 May 2024 08:00:11 +0000 Dario Strbenac via R-devel <r-devel at r-project.org> ?????: > Would a less resource-intensive value, such as 1, be a safer default > CPU value for confint? Which confint() method do you have in mind? There is at least four of them by default in R, and many additional classes could make use of stats:::confint.default by implementing vcov(). >

Hi, I am currently doing logistic regression analyses and I am trying to get confidence intervals for my partial logistic regression coefficients. Supposing I am right in assuming that the formula to estimate a 95% CI for a log odds coefficient is the following: log odds - 1.96*SE to log odds + 1.96*SE then I am not getting the right CI. For instance, this is a summary of my model: