search for: glim

After some futile searches, I decided to ask the list to see if any of the sages out there would have an answer: I have a function I wrote a few years ago in S, which calls glim numerous times. I'd like to port it to R, but glm works differently from glim, which takes as part of its input an X design matrix. I probably could write a function to convert glim to glm, but hope this wouldn't be necessary... Tim Liao

Dear Experts, In glim() of S Plus, one of the returned values is "var", the estimated variance matrix of coefficients. However, in glm() of R (there is no glim() in R), "var" is not one of the returned values. Anyone know what could I get the varience matrix of coefficients in glm() in R? As a novic...

Hi all, In my continuous transition of GLIM to R I try to make a glm with binomial errors. The data file have 3 vectors: h -> the factor that is ajusted (have 3 levels) d -> number of animais alive (the response) n -> total number of animals To test proportion of alive, make d/n. In GLIM: $yvar d$ $error binomial n$ $fit +h$...

Hi all I try to make a weibull survival analysis on R. I know make this on GLIM, and now I try to make the GLIM exercice GLEX8 on R to learning and compare the test. The variables are: time censor group bodymass In GLIM I make: $calc %s=1 $ to fit weibull rather than exponential $input %pcl weibull $ $macro model group*bodymass $endmac$ $use weibull t w %s $ Then, GLIM esti...

Dear All, I wonder if anyone can advise me as to whether there is a consensus as to how the effect size should be calculated from GLIM models in R for any specified significant main effect or interaction. In investigating the causes of variation in infection in wild animals, we have fitted 4-way GLIM models in R with negative binomial errors. These are then simplified using the STEP procedure, and finally each of the remaining te...

Hello, I would like to know if there is any package that allow us to fit Generalized Linear Models via Maximum Likelihood and Linear Models using Generalized Least Squarse in R as the functions glim and gls, respectively, from S-Plus. Also, anybody know if there is any package that fit Log-Linear Models using Generalized Least Squares? Any help will be very useful. Thanks, -- Frederico Zanqueta Poleto fred at poleto.com - ICQ# 4129787 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-...

Hi all I have another GLIM question. I have been using R as well as Genstat (version 6) in order to fit GLIM models to the data (displayed below). The same models are fitted but the answers supplied by the two packages are not the same. Why? Can anyone help? A discription of the data and the type of mod...

I've downloaded R for windows (9.0.1) and it is great! I've converted all my lecture notes for my GLM course to run on R (they are available on my web page below). I must admit I particularly like the default contrast options, which are identical to GLIM. Also I like the gl function - very useful! I have a couple of questions/bugs: 1. predict.glm doesn't work, but predict.lm does - actually all I am after is the equivalent of the GLIM $extract %vl command, which I want to get from vl<-predict.glm(glm,se.fit=T)$se.fit^2 A bit c...

I came to R from GLIM and its glm. My data sets (ecological community data) are severely over-dispersed, and so I was delighted to find out that the MASS library has glm.nb which is an advancement from the GLIM macros I had used (N.E.Breslow, Applied Statistics 33, 38--44; 1984). However, I need to use offset, but t...

...idered as nuisance term where parameter estimates are not needed. Could anyone point how absorbing individual effect could be carried out in glm. There is already code for Stata (http://statistics.open.ac.uk/sccs/stata/aglm.ado), Genstat (http://statistics.open.ac.uk/sccs/genstat%5Csccs.gen), Glim (http://statistics.open.ac.uk/sccs/glim/SCCS.MAC) , and SAS (http://statistics.open.ac.uk/sccs/sas/macro/poisreg.sas). Regards, Jari Haukka

...get the SSH banner displayed all the time when using e.g. CVS. Is there a way to set negative verbosity or to otherwise quell the banner information in SSH (or, worse, in CVS). I have tried ssh -q but that does _not_ quell the banner. Best Johan (I am not a regular subscriber so please cc to glimming--AT--kth--DOT--se)

...;), intercept=FALSE) which produced Error in glm.control(...) : unused argument(s) (intercept ...) Is there an easy way to do this? I suppose I could start hacking away at glm so it would take the argument and pass it on, but is it absent for a reason? Also, I noticed that S-Plus but not R has a glim routine that uses maximum likelihood. What would be the equivalent? Thanks.

Un bon mot s'il vous plait. I have coded an R routine to decompose messy data following Murray Aitkin and Brian Francis's NPMLE GLIM macros for the normal distribution only but extended to incorporate censoring and variance heterogeneity. Essentially it is a wrapper for nlm() in the M-part while the E-part re-estimates the weights in the same way as the GLIM macros. The big problem is that it is slow to run - even with homogen...

...My problem is related to how to measure probabilities from a probit model by changing one independent variable keeping the others constant. A simple toy example is like this Range for my variables is defined as follows y=0 or 1, x1 = -10 to 10, x2=-40 to 100, x3 = -5 to 5 Model output <- glim(y ~ x1+x2+x3 -1, family=binomial(link="probit")) outcoef <- output$coef xbeta <- as.matrix(cbind(x1, x2, x3) predprob <- pnorm(xbeta%*%outcoef) now I have the predicted probabilities for y=1 as defined above. My problem is as follows Keep X2 at 20 and X3 at 2. Then compute the...

Hello All: I hope I can get someone interested in this problem: Agresti in "Analysis of Categorical Data," p. 289, applies a "row and column effects model" to analyze a two-dimensional cross-classification of ordinal data. He got his results in either SAS or GLIM. Is there a way to replicate his results with R? He claims the RC model fits well with G^2(RC) = 3.57 with df = 8. The ML estimates for the row scores are (-1.11, -1.12, -0.37, 0.03, 1.01, 1.82) and the column estimates are (-1.68, -0.14, 0.14, 1.41) and beta = 0.17 Below, is the data: tbl.0 &l...

...t. glmmPQL() is in the ballpark of what I need, but once again seems to lack the "outer" variable specification that nlme() has, and which PROC GENMOD also has---and which I need. I read someplace of yags() that apparently uses GEE to estimate parameters of nonlinear models including GLIMs/mixed models, just the way PROC GENMOD (and many another program) does. But on trying to install it (either v4.0-1.zip or v4.0-2.tar.gz from Carey's site, or Ripley's Windows port) from a local, downloaded zip file (or tar.gz file converted to zip file), I always get an error saying:...

Hello R-helpers, I was wondering if anyone is porting S lib packages for design of experiments: conf.design, glim, graff(all from statlib)? I was able to change the format of S packages into R (including docs). In conf.design, by W. Venables, sort.list function is missing from R. I just put sort.list <- sort, but I got more error messages. Before doing more work, would like to know if this already done? R...

Hello R-helpers, I was wondering if anyone is porting S lib packages for design of experiments: conf.design, glim, graff(all from statlib)? I was able to change the format of S packages into R (including docs). In conf.design, by W. Venables, sort.list function is missing from R. I just put sort.list <- sort, but I got more error messages. Before doing more work, would like to know if this already done? R...

I am new to R so may well have missed the point somewhere. I would like to use an exponential error in my generalized linear model. It seems natural to restrict the Gamma family to do this ( and as one might in GLIM) by specifying the scale. This does not seem possible in R . Have I missed something? Sorry to raise such a trivial point but I am keen to specify the scale G.Janacek e-mail G.Janacek at uea.ac.uk School of Mathematics tel 44-(0)1603-592577 UEA, Norwich NR4 7TJ,UK...

Dear list, I am looking for a way to fix the scale parameter when fitting a generalized linear model with gamma errors and log link. Is there something like "SCALE" such as in GLIM? As always thanks a lot. Peter