similar to: get deviance from glm() for given parameter values

At 11:57 25/10/00 +0100, Brian Ripley wrote: >> Date: mer., 25 oct. 2000 12:38:55 +0200 >> From: Emmanuel Paradis <paradis@isem.univ-montp2.fr> > >> I think it would be nice to have par(ask=T) set by default in termplot(), >> like it is in plot.lm(). > >Well, it isn't really the default in plot.lm, the default for `ask' being > >interactive()

Ape is an R package for "analyses of phylogenetics and evolution". The first version (0.1) has been released on 27 August 2002 and is available on CRAN. >From the 'Description' file of version 0.1: Ape provides functions for reading, and plotting phylogenetic trees in parenthetic format (standard Newick format), analyses of comparative data in a

Dear R users, I am having some problems with glm. The first is an error message "subscript out of bounds". The second is the fact that reasonable starting values are not accepted by the function. To be more specific, here is an example: > success <- c(13,12,11,14,14,11,13,11,12) > failure <- c(0,0,0,0,0,0,0,2,2) > predictor <- c(0,80*5^(0:7)) >

There seems to be a bug with var() when the argument is a vector with exactly three values of 1e30 (or close to this value). This does not happen with twice, four (or more) times this value, or another value. > var(rep(1e30, 3)) [1] 2.971056e+28 > var(rep(1.2e30, 3)) [1] 2.971056e+28 > var(rep(0.9e30, 3)) [1] 2.971056e+28 > var(rep(0.8e30, 3)) [1] 0 > var(rep(1e29, 3)) [1] 0 >

Hi there, I have been having trouble running negative binomial regression (glm.nb) using library MASS in R v2.15.0 on Mac OSX. I am running multiple models on the variables influencing the group size of damselfish in coral reefs (count data). For total group size and two of my species, glm.nb is working great to deal with overdispersion in my count data. For two of my species, I am getting a

Hi, I think it would be nice to have par(ask=T) set by default in termplot(), like it is in plot.lm(). Best, Emmanuel Paradis -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !)

Hello R-users. I haven't use R for a life time and this might be trivial - I hope you do not mind. I have a questions about arguments in the Glm-function. There seems to be something that I cannot cope. The basics are ok: > y <- as.double(rnorm(20) > .5) > logit.model <- glm(y ~ rnorm(20), family=binomial(link=logit), trace = TRUE) Deviance = 28.34255 Iterations - 1

Hi all, I am trying to understand how is calculated the AIC returned by glm(). I have a model object m1 which fitting results are: > summary(m1) [...] (Dispersion parameter for gaussian family taken to be 3.735714) Null deviance: 1439.8 on 15 degrees of freedom Residual deviance: 52.3 on 14 degrees of freedom AIC: 70.357 Since there are 2 parameters, I would naively compute: AIC

Dear R-users, Thanks to Friedrich Leisch, my document "R pour les d?butants" is available on CRAN in the contributed documentation section: http://cran.r-project.org/doc/contrib/Rdebuts.pdf. It is written in French. "R pour les d?butants" ("R for beginners") gives a starting point for people with no experience with R (or S). I tried to explain the basics in the

Dear R-users, Thanks to Friedrich Leisch, my document "R pour les d?butants" is available on CRAN in the contributed documentation section: http://cran.r-project.org/doc/contrib/Rdebuts.pdf. It is written in French. "R pour les d?butants" ("R for beginners") gives a starting point for people with no experience with R (or S). I tried to explain the basics in the

Full_Name: Emmanuel Paradis Version: 2.4.0 OS: Linux Submission from: (NULL) (193.49.41.124) Adding text to a plot makes R freeze if 'srt' is given a very small negative value, eg: plot(1, type = "n") text(1, 1, "some text....", srt = -1e-8) But if 'srt = -1e-6' (or smaller) or 'srt = -1e-19' (or greater), this works. This seems to be OS-dependent:

At 19:48 07/06/00 +0200, Friedrich Leisch wrote: >>>>>> On Wed, 7 Jun 2000 09:41:23 -0700 (PDT), >>>>>> Thomas Lumley (TL) wrote: > > >TL> Some of this can be done with apropos(), but I don't think you can keyword >TL> search from inside R. It would be nice. > > >help.search() might do what you want ... > >.f Yes, but

G'day all, I had a look at the GLM code of R (1.4.1) and I believe that there are problems with the function "glm.fit" that may bite in rare circumstances. Note, I have no data set with which I ran into trouble. This report is solely based on having a look at the code. Below I append a listing of the glm.fit function as produced by my system. I have added line numbers so that I

When reading a file with scan(), the following crashes R under Solaris and WinNT 4.0 (versions below): > ads <- scan("Bltiadu.dat", what=list(,,)) Would an error message be more logical? Note that the followings work (the data file has 201 lines and 3 columns): > ads <- scan("Bltiadu.dat", what=list(0,,)) Read 603 lines > ads <-

Hello, I have a question regarding estimation of the dispersion parameter (theta) for generalized linear models with the negative binomial error structure. As I understand, there are two main methods to fit glm's using the nb error structure in R: glm.nb() or glm() with the negative.binomial(theta) family. Both functions are implemented through the MASS library. Fitting the model using these

I have a data with binary response variable, repcnd (pregnant or not) and one predictor continuous variable, svl (body size) as shown below. I did Hosmer-Lemeshow test as a goodness of fit (as suggested by a kind “R-helper” previously). To test whether the predictor (svl, or body size) has significant effect on predicting whether or not a female snake is pregnant, I used the differences between

Dear all, Are there functions or packages in R that can handle interval-censored data? I have looked in various packages (such as survival5 or event), but it seems that only right-censored data can be analysed. More generally, are there methods to analyse both interval-censored observations and right-censored observations in the same data set? Thanks in advance. Emmanuel Paradis

Full_Name: Ben Cooper Version: 1.5.0 OS: linux Submission from: (NULL) (134.174.187.90) The help page for glm.nb (in MASS package) says that it takes "Any other arguments for the glm() function except family" One such argument is start "starting values for the parameters in the linear predictor." However, when called with starting values glm.nb returns: Error in

I am using glm.nb, a ~b*c ( b is categorical and c is continuous). when I run this model I get the warning message: Warning messages: 1: In theta.ml(Y, mu, sum(w), w, limit = control$maxit, trace = control$trace > : iteration limit reached 2: In theta.ml(Y, mu, sum(w), w, limit = control$maxit, trace = control$trace > : iteration limit reached What does this mean? -- Graduate

dear List: glm(a~b+c,family=binomial,data=x)->fit deviance(fit) returns the same as the residual deviance. I don't not know much about logistic regression.Some book tells that: " Deviance (likelihood ratio statistic): Deviance = -2log( likelihoodof the currentmodel /likelihoodof thesaturated model) Note: (1). The current model is the model of interest. (2). The saturated model