search for: glmrob

Dear List members, I am runnning a logistic regression that includes sample weights (expressed by a variable called WEIGHT) using glmob (from robustbase). My model looks like this: B12<-glmrob(SERE~COMP+COM,family=binomial,weights=WEIGHT) When I include the weights, my standard error columns, as well as the p-values, show only NAs. If I exclude weights=WEIGHTS, everything works. I would like to use the weights. Does anyone know what could be the problem? Thanks in advance...

Dear list members, I have been doing robust regressions in R, using the MASS package for rlm and robustbase for logistic regressions. I must be doing something wrong, because my output does not include r-squares (or adjusted r-squares), or, in the case of glmrob, -2log likelihoods. Does anyone know how to get an output that includes these? Thanks so much for the help Celso -- Celso F. Rocha de Barros DPhil candidate in Sociology, University of Oxford [[alternative HTML version deleted]]

...I have a bunch of data which is assumed to be instances of a geometric random variable with outliers. How can I do a robust estimation of the parameter p so that the effect of outliers is minimized? As a part of the estimation process, I also need to know which are the outliers in the data. I found glmrob which does robust estimation of Poisson and binomial random variables but not geometric random variable. I understand that the maximum likelihood estimate of p of geometric random variable is the mean of the instance values. So if we do robust estimate of mean of the instance values, can we say th...

Hello R-help, According to a research article that covers the topic I'm analyzing, in Stata, a Poisson pseudo-maximum-likelihood (PPML) estimation can be obtained with the command poisson depvar_ij ln(indepvar1_ij) ln(indepvar2_ij) ... ln(indepvarN_ij), robust I looked up Stata help for the command, to understand syntax and such: www.stata.com/help.cgi?poisson Which simply says