similar to: Interpreting messages when building packages

I am trying to plot the results of a random effects model where each subject is allowed to have his, or her, own intercept. I use xyplot to plot the data, lme to compute the regression and then try to put a summary regression line on the xyplot. As can be seen by the output pasted below, I am getting an error message, Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) : (list)

Full_Name: José Otero Version: Version 1.5.0 (2002-04-29) OS: Redhat 7.3 Submission from: (NULL) (192.187.16.164) Hi: Installation of package faraway as root, from tarbal: R CMD INSTALL ./faraway.tar.gz ERROR: cannot extract package from './faraway.tar.gz' idem, from zipped package: R CMD INSTALL faraway.zip gzip: faraway.zip has more than one entry--rest ignored ERROR: cannot

... but do note: glm(lot1 ~ log(u), data = clotting, family = gaussian) is a plain old *linear model*, which is of course a specific type of glm, but not one that requires the machinery of glm() to fit. That is, the above is exactly the same as: lm(lot1 ~ log(u), data = clotting) and gives exactly the same sigma() ! (and I would therefore hazard the guess that the poster may misunderstand

Dear all, I'm trying to use the "optim" function to replicate the results from the "glm" using an example from the help page of "glm", but I could not get the "optim" function to work. Would you please point out where I did wrong? Thanks a lot. The following is the code: # Step 1: fit the glm clotting <- data.frame( u =

Hi, I have below GLM fit clotting <- data.frame( u = c(5,10,15,20,30,40,60,80,100), lot1 = c(118,58,42,35,27,25,21,19,18), lot2 = c(69,35,26,21,18,16,13,12,12)) summary(glm(lot1 ~ log(u), data = clotting, family = gaussian)) Is there any direct function to extract estimate of Error standard deviation?

Hello, silly question I suppose, but somehow I can't manage to extract the probabilities from a glm.predict() result: > str(res) Named num [1:9] 0.00814 0.01877 0.025 0.02941 0.03563 ... - attr(*, "names")= chr [1:9] "1" "2" "3" "4" ... I got from: # A Gamma example, from McCullagh & Nelder (1989, pp. 300-2) clotting <-

Anyone conceive of any reason why I should have a stream that RealPlayer and iTunes have no problem with, but MP9 refuses to play: just sits there dumbly having loaded the .m3u that points to it, ignoring the play button?

vcov(). ? On Tue, Dec 24, 2024, 8:45 AM Christofer Bogaso <bogaso.christofer at gmail.com> wrote: > Hi, > > I have below GLM fit > > clotting <- data.frame( > u = c(5,10,15,20,30,40,60,80,100), > lot1 = c(118,58,42,35,27,25,21,19,18), > lot2 = c(69,35,26,21,18,16,13,12,12)) > summary(glm(lot1 ~ log(u), data = clotting, family = gaussian)) > >

I think vcov() gives estimates of VCV for coefficients. I want estimate of SD for residuals On Tue, Dec 24, 2024 at 7:24?PM Ben Bolker <bbolker at gmail.com> wrote: > > vcov(). ? > > > On Tue, Dec 24, 2024, 8:45 AM Christofer Bogaso <bogaso.christofer at gmail.com> wrote: >> >> Hi, >> >> I have below GLM fit >> >> clotting <-

?deviance ?anova Bert On Tue, Dec 24, 2024 at 6:22?AM Christofer Bogaso <bogaso.christofer at gmail.com> wrote: > > I think vcov() gives estimates of VCV for coefficients. > > I want estimate of SD for residuals > > On Tue, Dec 24, 2024 at 7:24?PM Ben Bolker <bbolker at gmail.com> wrote: > > > > vcov(). ? > > > > > > On Tue, Dec 24,

Hello, I am trying to figure out how to plot the profile likelihood curve of a GLM parameter with 95% pCI's on the same plot. The example I have been trying with is below. The plots I am getting are not the likelihood curves that I was expecting. The y-axis of the plots is tau and I would like that axis to be the likelihood so that I have a curve that maxes at the parameter estimate. I am

I am experiencing a curious event, and wondering if others have seen this... As well, I have a question related to it. Today, I noticed my puppet summary report from Foreman this morning, that 60 of my 160 hosts all stopped reporting at nearly the exact same time, and have not since restarted. Investigating, it appears that my puppetmaster temporarily ran out of disk space on the /var

Dear Helper: I am using R to finish a project which is near the dealine. Please help me !!!!! I need to construct a table. The name of the table is the sequence from 1 to 7 with some missing values arbitrarily. For example 1 to 7 1 2 3 6 7 12 3 45 5 7 I want to add the missing numbers of the title which should be seq(1,7) In this case, 4 and 5 and the corresponding data is

Hi R users, I want to use dglm Package. I run the examples and it give me an error: Error en dglm(lot1 ~ log(u), ~1, data = clotting, family = Gamma) : no se pudo encontrar la funci?n "as.family" dglm can't find "as.family" function why ? Thank you for your help

Dear ExpRts, I would like to perform a function with two arguments over the rows of two matrices. There are a couple of *applys (including mApply in Hmisc) but I haven't found out how to do it straightforward. Applying to row indices works, but looks like a poor hack to me: sens <- function(test, gold) { if (any(gold==1)) { sum(test[which(gold==1)]/sum(which(gold==1))) } else NA }

Dear expRts, I just realized that the "..." argument in a function cannot be used without taking precautions sometimes. The following behaviour is what I stumbled upon: > myrepl <- function(length, fun, ...) { + replicate(length, fun(...))} > myrepl(20, sample, 1:5) [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 > myotherrepl <- function(length, fun, ...) { + args <-

Hi, I have a data set (weight) that does not follow the Gaussian (Normal) distribution. However, I have to transform the data before applying the Gaussian distribution. I used this syntax and used log(weight) as: posJy.model<-glm(log(weight) ~ factor(pos), family=gaussian(link='identity'), subset=Soil=="Jy"). This syntax COULD NOT transform the data. But if I transform the

I am trying to save an R data.frame as an Excel sheet. I do NOT want the column names saved into row 1. I set colnames=F. However, it still seems that the colnames are saved into row 1. Is this a bug? Or am I coding incorrectly and.or misunderstanding this feature? #example code: sheet = "c:/test2.xls" temp=data.frame(matrix(data=NA,nrow=10,ncol=15)) temp[1,1] =

Whenever I review audit logs, it is difficult for me to determine if an account was logged in at an usual day/time because there is no timestamp next to any entry, at least as I interpret the format. How, then do I properly and successfully review the audit log entries based on a date/time stamp? Also, how can I filter out root and sudo account entries, displaying everyone else in audit?

i''ve got a situtation where i''m trying to pass arguments from a method to find and AR is telling me that it can''t find the record where id=all here''s what i am attempting to do class Thing < ActiveRecord::Base belongs_to :x end class FlyingThing < Thing end class x < ActiveRecord::Base has_many :things do def that_fly(*args)