similar to: How to 'mute' a function (like confint())

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:

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)

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

? 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(). >

Dear R developers, I noticed a bug in the stats4 package, specifically in the confint method applied to ?mle? objects. In particular, when some ?fixed? parameters define the log likelihood, these parameters are stored within the mle object but they are not used by the ?confint" method, which retrieves their value from the global environment (whenever they still exist). Sample code: >

the function confint uses the profiling method of the function of the package MASS confint.glm even after the package has been detached! 1: might this be the intenden behavior? 2. How does the function remember its 'MASS' functionality after detaching the package? R: 1.8.0; Windows 2000 Here is a sample program > set.seed(7882) > x<-rep(c(0,1),c(20,20)) >

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

Full_Name: Christian Lajaunie Version: 2.5.1 OS: Fedora fc6 Submission from: (NULL) (193.251.63.39) confint() does not use the appropriate variance term when the design matrix contains a zero column (which of course should not happen). Example: A 10x2 matrix with trivial column 1: > junk <- data.frame(x=rep(0,10), u=factor(sample(c("Y", "N"), 10, replace=T))) The

Dear all, I have run the confint() function according to below and I get the following error message: > confint(stepAIC.glm.spe.var.konn2.abund, level=0.95) Waiting for profiling to be done... Error: missing value where logical needed In addition: Warning message: NaNs produced in: sqrt((fm$deviance - OriginalDeviance)/DispersionParameter) or > confint(stepAIC.glm.spe.var.konn2.abund,

Hello, Would a less resource-intensive value, such as 1, be a safer default CPU value for confint? I noticed excessive CPU usage on a I.T. administrator-managed server which was being three-quarters used by another staff member when the confidence interval calculation in an R Markdown document suddenly changed from two seconds to ninety seconds because of competition for CPUs between users. Also,

I am unable to calculate confidence intervals for the slope estimate in a quasibinomial glm using confint(). Below is the output and the package info for MASS. Thanks in advance! R 2.9.2 MASS 7.2-48 > confint(glm.palive.0.str) Waiting for profiling to be done... Error: dims [product 37] do not match the length of object [74] > glm.palive.0.str Call: glm(formula = cbind(alive, red) ~ str,

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

I have the following binary data set: Sex Response 0 1 0 159 162 1 4 37 My commands library(MASS) sib.glm=glm(sib~sex,family=binomial,data=sib.data) summary(sib.glm) The coefficients in the output are Estimate Std. Error z value Pr(>|z|) (Intercept) -3.6826 0.5062 -7.274 3.48e-13

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

Greetings all, I was in the process of creating a function to generate profile likelihood confidence intervals for a proportion using a binomial glm. This is a component of a larger function to generate and plot confidence intervals for proportions using the above, along with bootstrap (BCa), Wilson and Exact to visually demonstrate the variation across the methods to some folks. I had initially

On July 12, 2004 Spencer Graves wrote an email describing essentially the same issue that I would like help on: calling the confint function from within another homemade function. Because he provided many good examples of the problem, I will not reproduce them here but will instead refer readers to the original posting: http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg23826.html It is

Dear colleagues, I have used statistical software "R" in academic research, and I find very interesting. So now I have started my studies at advanced level. I have conducted several statistical models of the type "*nls*". In respect of procedures for models of the type nls, I'd like you answer only one question that I have had doubts, related to the formula

Hi all, I've got a list (Reg3Lst) with 1000 nls regression results in it. I'd like to get the confidence interval of the parameters obtained with the nonlinear regressions. Thus I've used this: for (i in 1:1000) { foo<-list(foo,confint(Reg3Lst[[i]])) } For some regressions the confidence interval is not estimated because of a singular gradient result. Then it

I fit a proportional odds model with the polr-function of the MASS package from Venables and Ripley Applying the confint method to calculate confidence intervals for the parameters I get the following error message Waiting for profiling to be done... Re-fitting to get Hessian Error in X[, -i, drop = FALSE] : incorrect number of dimensions Can someone explain the error-message? (The

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: