similar to: confint: which method attached?

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

fixed @ R-forge. New version should appear on CRAN soon. Thanks for the report! Torsten > > ---------- Forwarded message ---------- > Date: Sat, 3 Sep 2011 23:56:35 +0200 > From: Ulrich Halekoh <Ulrich.Halekoh at agrsci.dk> > To: "r-help at r-project.org" <r-help at r-project.org> > Subject: [R] glht (multcomp): NA's for confidence intervals using

Using a factor with 'number' levels the straightforward symbolic formulation of a contrast in 'glht' of the 'multcomp' package fails. How can this problem be resolved without having to redefine the factor levels? Example: #A is a factor with 'number' levels #B similar factor with 'letter' levels dat<-data.frame(y=1:4,A=factor(c(1,1,2,2)),

Hej, Calculation of confidence intervals for means based on a model fitted with lmer using the package multcomp - yields results for calpha=adjusted_calpha - NA's for calpha=univariate_calpha Example: library(lme4) library(multcomp) ### Generate data set.seed(8) d<-expand.grid(treat=1:2,block=1:3) e<-rnorm(3) names(e)<-1:3 d$y<-rnorm(nrow(d)) + e[d$block]

Dear all, the application of the function rstandard() in the base package to a glm object does not produce residuals standardized to have variance one: the reason is that the deviance residuals are divided by the dispersion estimate and not by the square root of the estimate for the dispersion. Should the function not be changed to produce residuals with a variance about 1? R 1.8.1 on

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:

>>>>> steven pav >>>>> on Thu, 19 Jul 2018 21:51:07 -0700 writes: > It seems that confint.default returns an empty data.frame > for objects of class mlm. For example: > It seems that confint.default returns an empty data.frame for objects of > class mlm. Not quite: Note that 'mlm' objects are also 'lm' objects, and so it is

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:

Dear R-helpers, I am using confint() within a function, and I want to turn off the message it prints: x <- rnorm(100) y <- x^1.1+rnorm(100) nlsfit <- nls(y ~ g0*x^g1, start=list(g0=1,g1=1)) > confint(nlsfit) Waiting for profiling to be done... 2.5% 97.5% g0 0.4484198 1.143761 g1 1.0380479 2.370057 I cannot find any way to turn off 'Waiting for. .." I tried

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

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

On Mon, Mar 13, 2017 at 11:48:05PM +0200, Keresztes Péter-Zoltán wrote: > Hello, > > We have a nodejs app which is injecting first boot scripts using virt-customize however the exact same commands are working when triggered manually. > > Here is the debug output of the commands Which version of virt-customize? A number of bugs were fixed in this part of the code in the last

Hi there, I had a problem when I hoped to get confidence intervals for the parameters I got using mle() of stats4 package. This problem would not appear if ``fixed'' option was not used. The following mini-example will demo the problem: x <- c(100, 56, 32, 18, 10, 1) r <- c(18, 17, 10, 6, 4, 3) n <- c(18, 22, 17, 21, 23, 20) loglik.1 <- function(alpha, beta, c) { x

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

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

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: >

I am running libguestfs version 1.34.2 The issue is the following. When I start the vm with virt-log I see this: Mar 13 17:33:30 multi6 firstboot.sh[358]: /usr/lib/virt-sysprep/firstboot.sh start Mar 13 17:33:30 multi6 cron[359]: (CRON) INFO (Running @reboot jobs) Mar 13 17:33:30 multi6 firstboot.sh[358]: Scripts dir: /usr/lib/virt-sysprep/scripts Mar 13 17:33:30 multi6 firstboot.sh[358]: ===

I want to label groups of points in the plot of residuals against predicted values generated by plot.lm(). Labelling the points by color x<-1:15 y<-rnorm(15) f<-factor(rep(c(1:3),each=5)) g<-glm(y~x) plot(g,which=1,col=c(1,2,3)[f]) I receive the error message Error in title(main, sub, xlab, ylab, line, outer, ...) : graphical parameter "col" has the wrong

Another easy(/stupid) question: with the following command j2<-xf1[1:10,"V4"] I have > j2 [1] CHROMOLI LINEAGERMAI RINALDI GIUNTIMA AUTOSTELLA [6] CAIZZONE CENTRO B PEL E C SNC CONSORZI MAN NORD PDM 1304 Levels: MACHIAVELLI Snc MENARINI MANUFACTURERS LOGISTICS SERVICES ... ZUCCHERIFICIO

Dear R users, There is a new version (1.5-1) of the Rcmdr package. Here, from the CHANGES files, are changes since the last minor version (1.4-0) was released a year ago: ------------------------------------------------------- Version 1.4-1 o The following updated translations have been added: Catalan (thanks to Manel Salamero), French (thanks to Philippe Grojean), Japanese (thanks to