similar to: How do I set the dispersion parameter in poisson glm?

Hi, everyone. I have what I hope will be a simple coding question. It seems this is a common job, but so far I've had trouble finding the answer in searches. I have two matrices (x and y) with a different number of observations in each. I need to draw a random sample without replacement of observations from x, and then, using a matching variable, draw a sample of equal size from y. It is the

Dear R community, I am new to R, a reforming SAS user :) I am running R 2.10.1 on a Windows XP machine. I would like to write linear functions of my coefficient parameter estimates from a glm, but am having a difficult time understanding the parameterization R uses. In the toy example below I am running a glm on binomial data, with clones and lines within clones as fixed effects, each with 6

Sorry about re-posting this, it never went out to the mailing list when I posted this to r-help forum on Nabble and was pending for a few days, now that I am subscribe to the mailing list I hope that this goes out: I've been a viewer of this forum for a while and it has helped out a lot, but this is my first time posting something. I am running glm models for richness and abundances. For

Hi, I would like to obtain the dispersion parameter for a quasipoisson model for later use in calculating QAIC values for model comparison.Can anyone suggest a method of how to go about doing this? The idea I have now is that I could use the residual deviance divided by the residual degrees of freedom to obtain the dispersion parameter. The residual deviance is available in the summary

Hi, I'm new to R and GLMMs, and I've been unable to find the answers to my questions by trawling through the R help archives. I'm hoping someone here can help me. I'm running an analysis on Seedling survival (count data=Poisson distribution) on restoration sites, and my main interest is in determining whether the Nutrients (N) and water absorbing polymer Gel (G) additions to the

Dear all, Using the quasibinomial and quasipoisson families results in no AIC being calculated. However, a quasi AIC has actually been defined by Lebreton et al (1992). In the (in my opinon, at least) very interesting book by Burnham and Anderson (1998,2002) this QAIC (and also QAICc) is covered. Maybe this is something that could be implemented in R. Take a look at page 23 in this pdf:

Hello R-list. I am a "long time listener - first time caller" who has been using R in research and graduate teaching for over 5 years. I hope that my question is simple but not too foolish. I've looked through the FAQ and searched the R site mail list with some close hits but no direct answers, so... I would like to estimate QAIC (and QAICc) for a glm fit using the

*************************************************************************************************** CISTI'2013 DOCTORAL SYMPOSIUM 8th Iberian Conference on Information Systems and Technologies Lisbn, Portugal, June 19 - 23, 2013 http://www.aisti.eu/cisti2013/index.php?option=com_content&view=article&id=64&Itemid=68&lang=en

*************************************************************************************************** CISTI'2013 DOCTORAL SYMPOSIUM 8th Iberian Conference on Information Systems and Technologies Lisbn, Portugal, June 19 - 23, 2013 http://www.aisti.eu/cisti2013/index.php?option=com_content&view=article&id=64&Itemid=68&lang=en

I am creating habitat selection models for caribou and other species with data collected from GPS collars. In my current situation the radio-collars recorded the locations of 30 caribou every 6 hours. I am then comparing resources used at caribou locations to random locations using logistic regression (standard habitat analysis). The data is therefore highly autocorrelated and this causes Type

Hi list, can anybody point me to the trick how glm is computing the dispersion parameter in quasi-poisson regression, eg. glm(...,family="quasipoisson")? Thanks &regards, Sven

Dear list, I am trying to use MuMIn to compare all possible mixed models using the dredge function on binomial data but I am getting an error message that I cannot decode. This error only occurs when I use glmer. When I use an lmer analysis on a different response variable every works great. Example using a simplified glmer model global model: mod<- glmer(cbind(st$X2.REP.LIVE,

Hi, I'm new to R and GLMMs, and I've been unable to find the answers to my questions by trawling through the R help archives. I'm hoping someone here can help me. I'm running an analysis on Seedling survival (count data=Poisson distribution) on restoration sites, and my main interest is in determining whether the Nutrients (N) and water absorbing polymer Gel (G) additions to the

Following p.206 of "Statistical Models in S", I wish to change the code for summary.glm() so that it estimates the dispersion for binomial & poisson models when the parameter dispersion is set to zero. The following changes [insertion of ||dispersion==0 at one point; and !is.null(dispersion) at another] will do the trick: "summary.glm" <- function(object, dispersion =

Lista aprovados Maravilha: Amamba?: ANDERSON BEZERRA MOURAO, LUCAS CAULA ALBUQUERQUE, GEILSON HOLANDA SAMPAIO, RAFAEL FERNANDES, JO?O CARLOS MOREIRA DE CARVALHO, DEBORA CRISTINA SCHNORNBERGER, MARIA MACLENE BEZERRA LIMA, JOAO PEDRO TAVARES MAGALHAES. TAMYRES AMORIM SOUZA, CAIO CESAR FERNANDES LOPES, MAGNUN SANTOS FREDERICO, IAGO SIMOES CALIARI, RITA MARIA SILVA ALMEIDA. Pedreiras. Maravilha,

Hi I have folowed this guide http://www.enterprisenetworkingplanet.com/netos/article.php/3457461 to import users from my NT4 domain to a debian sarge with samba 3.0.14a Everything runs fine till the net rpc vampire command, some users give an error others are imported fine. I don't see any problem on this users configuration in the NT4 server, here is part of the output: thanks.

Hi I have folowed this guide http://www.enterprisenetworkingplanet.com/netos/article.php/3457461 to import users from my NT4 domain to a debian sarge with samba 3.0.14a Everything runs fine till the net rpc vampire command, some users give an error others are imported fine. I don't see any problem on this users configuration in the NT4 server, here is part of the output: thanks.

1. I'm attempting to test for Random Effects. I've grouped the data on subject (grid) but want to use lme to build the model without subject as a RE then add it and do anova between the 2 models. This is the result I get and it appears it's adding Random Effects. tmp.dat4 <- groupedData(Trials ~ 1 | grid, data = tmp.dat4) mod2a <- lme(Trials ~ factor(group_id) + reversal,

*************************************************************************************************** CISTI'2013 DOCTORAL SYMPOSIUM 8th Iberian Conference on Information Systems and Technologies Lisbon, Portugal, June 19 - 23, 2013 http://www.aisti.eu/cisti2013/index.php?option=com_content&view=article&id=64&Itemid=68&lang=en

*************************************************************************************************** CISTI'2013 DOCTORAL SYMPOSIUM 8th Iberian Conference on Information Systems and Technologies Lisbon, Portugal, June 19 - 23, 2013 http://www.aisti.eu/cisti2013/index.php?option=com_content&view=article&id=64&Itemid=68&lang=en