similar to: Sweave glm.fit

Hi everybody, I wanted to use Sweave but I do not have the Latex package: "LaTeX Error: File 'Sweave.sty' not found." I cannot find it with MiKTeX :-( Can somebody help me ? Thanks a lot, Jimmy [[alternative HTML version deleted]]

Dear R users, I am using the Sweave package and I am doing some MCMC. I have a loop function for my MCMC. Every 100 iterations, I want the number of iterations already done to appear on my screen (but not on the final document). Is that possible ? Usually I can rely on > if (i%%100==0) cat(i, "\n") but not when using Sweave. Thanks for your help, Jimmy [[alternative HTML

Hi everybody, I wanted to name a column vector (a variable). This is what I did : try<-matrix(1:4,nrow=4,ncol=1) attr(try,"dimnames")<-list(NULL,"true value") Is it OK ? Thanks for your help, Jimmy [[alternative HTML version deleted]]

What kind of special magic does glm have? I'm working on a logistic regression solver (L-BFGS) in c and I've been using glm to check my results. I came across a data set that has a very high condition number (the data matrix transpose the data matrix) that when running my solver does not converge, but the same data set with glm was converging ( I love R :) ). I noticed that glm using

Hi everybody, How can I set the seed for my simulations ? Is "set.seed(123456)" alright ? Thanks a lot, Jimmy [[alternative HTML version deleted]]

Hi all, I am doing bootstrap with logistic regression by using glm function, and I get the errors; glm.fit: fitted probabilities numerically 0 or 1 occurred and glm.fit: algorithm did not converge I have read some things about this issue in the mailing list. I can guess what was the problem. My data contains one or may be two outliers. Does the error occur due to these extreme values or

In trying to change the driver used by Sweave on the command line using R CMD Sweave --driver=foo I consistently get the "directory 'foo' does not exist' error. (For any value of 'foo', even the default 'RweaveLatex'.) Looking up the source code for function .Sweave that is called by 'R CMD Sweave', I notice that the argument 'driver', if

Hi all I am preparing a document using Sweave; a really useful tool. But I am having a problem. Consider this toy example Sweave file: \documentclass{article} \begin{document} <<echo=TRUE,results=verbatim>>= options(width=40) # Set width to 40 characters hide <- capture.output(example(glm)) # Create an example of the problem, but hide the output summary(glm.D93) #

Full_Name: Bonnie Version: 1.6.1 OS: Windows Submission from: (NULL) (160.129.25.106) glm() seems to converge, even when it shouldn't. I am trying to fit a model where $converge=FALSE and I am fitting models that do not converge in SAS, but they seem to converge in R ... Thank you.

Hi, When I run the following code : Y <- c(rep(0,35),1,2,0,6,8,16,43) cst <- log(choose(42, 42:1)) beta <- 42:1 tau <- (beta^2)/2 fit <- glm(formula = Y ~ offset(cst) + beta + tau, family = poisson) fit fit$converged glm prints a warning saying that the algorithm did not converge. However, fit$converged takes the value TRUE. I don't understand why fit$converged is not

I'm working on a Latex document with lots of R code in it, so naturally enough it would be a good idea to use SWeave. But then I don't get to see the output as I'm editing. Or do I? Is there a tool to process a .Rnw file and incorporate the output from the commands into it (in a form that is not used for producing the output .tex file, but which is updated each time I process

Hi, as far as I understand it, the new R devel feature of processing non-Sweave vignettes will (a) locate any "[.][RrSs](nw|tex)$" or ".Rmd" files, (b) check for a registered vignette engine, (c) process the file using the registered "weave" function, (d) and possibly post process the generated weave artifact (e.g. a *.tex file). I'd like to propose to extend

DeaR R-useRs, I'm trying to fit a logist model with these data: > dati y x 1 1 37 2 1 35 3 1 33 4 1 40 5 1 45 6 1 41 7 1 42 8 0 20 9 0 21 10 0 25 11 0 27 12 0 29 13 0 18 I use glm(), having this output: > g<-glm(y~x,family=binomial,data=dati) Warning messages: 1: Algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart =

I am analysing parasite egg count data and am having trouble with glm with a negative binomial family. In my first data set, 55% of the 3000 cases have a zero count, and the non-zero counts range from 94 to 145,781. Eventually, I want to run bic.glm, so I need to be able to use glm(family= neg.bin(theta)). But first I ran glm.nb to get an estimate of theta: > hook.nb<- glm.nb(fh,

Hi, Recently I saw a couple of cases in which the package vignettes were somewhat complicated so that Stangle() (or knitr::purl() or other tangling functions) can fail to produce the exact R code that is executed by the weaving function Sweave() (or knitr::knit(), ...). For example, this is a valid document that can pass the weaving process but cannot generate a valid R script to be source()d:

Hello, When I run the following glm model: modelresult=glm(CID~WS+SS+DV+DS, data=kimu, family=binomial) I get the following warning messages: 1: glm.fit: algorithm did not converge 2: glm.fit: fitted probabilities numerically 0 or 1 occurred What I am trying to do is model my response variable (CID: correct bird identification) as a function of the predictor variables weather state (WS), sea

Dear All, I'm trying to use waldtest to test poolability (parameter stability) between two logistic regressions. Because I need to use robust standard errors (using sandwich), I cannot use anova. anova has no problems running the test, but waldtest does, indipendently of specifying vcov or not. waldtest does not appear to see that my models are nested. H0 in my case is the the vector of

Hello, I'm learning to use Sweave, and I've run into a problem: sometimes, when entering long lines of input and using long variable names, Sweave will not insert linebreaks in a way that respects the width setting. This causes undesirable overflows into the margins in the latex file. For example, consider the following document (adapted from the GLM example): \documentclass{article}

Dear List, With regard to the question I previously raised, here is the result I obtained right now, brglm() does help, but there are two situations: 1) Classifiers with extremely high AIC (over 200), no perfect separation, coefficients converge. in this case, using brglm() does help! It stabilize the AIC, and the classification power is better. Code and output: (need to install package:

Dear R-team As I didn't get any answer to my bug-report last week I have taken the effort and extracted a minimal data set from my data (see below) where the following bug occurs: > glm(SKR.ein.aus ~ ., family = binomial, data = bugdata, na.action = na.omit) Error in names<-.default(*tmp*, value = ynames) : names attribute must be the same length as the vector In addition: Warning