similar to: generalized negative binomial

Hello; Does anybody knows that R have a function for Generelized Negative Binomial model, something like "gnbreg" in "STATA" where dispersion parameter itself is a function of covaraites ? Thanks; [[alternative HTML version deleted]]

Dear All, I have been struggling to understand why for the housing data in MASS library R and stata give coef. estimates that are really different. I also tried to come up with many many examples myself (see below, of course I did not have the set.seed command included) and all of my `random' examples seem to give verry similar output. For the housing data, I have changed the data into numeric

hello everybody solved the problem with summary, now I have another one eg I estimate > try.op <- polr( > as.ordered(sod.sit.ec.fam) ~ > log(y) + > log(1 + nfiglimin) + > log(1 + nfiglimagg) + > log(ncomp - nfiglitot) + > eta + > I(eta^2) + >

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,

I have spent a fair amount of time looking for a package that is automated to run glm (binomial) regression models with all possible subsets of my independent variables. Something akin to Lumley's "leaps" package, but can be applied to glms, not just lms; or something similar to Stata's brute force "tryem" function? If anyone can point me in the right direction I

I have seen several queries about parameterizing the negative binomial scale parameter. This is called the heterogeneous negative binomial. I have written a function called "nbinomial" which is in the msme package on CRAN. Type ?nbinomial to see the help file. The default model is a negative binomial for which the dispersion parameter is directly related to mu, which is how Stata,

I have a case where the easiest way to draw a particular symbol would be to draw something a little bigger, and then use polygon(... , col=0) to erase the extra stuff. Just how to do this best when par('bg') = 'transparent' is, however, eluding me. I've looked through the archives and the book R Graphics without quite seeing the light. Help or pointers to help would be

Hello, I am trying to run a negative binomial regression model in R and can't get the standard errors to match the output I get from the Stata nbreg command. I've tried a few different options but haven't had much luck. The closest I've found is: gamlss(formula, family = NBI, sigma.formula = ~ 1,data=dataframe) ...But this is still a little off most of the time and pretty far

I looked for examples of count data that might interest the students and found this project about dropout rates in Los Angeles High Schools. It is discussed in the UCLA stats help pages for the Stata users: http://www.ats.ucla.edu/stat/stata/library/count.htm and See: http://www.ats.ucla.edu/stat/stata/library/longutil.htm To replicate those results, I used R's excellent foreign package to

Matteo, I fully agree with David: please read the posting guide. Anyway, the error message says it all: "the estimated variance of the individual effect is negative". See e.g. the "basic panel" chapter (10 or 11) in Wooldridge's "Econometric Analysis of XS and Panel Data" to understand why this may happen. Stata's behaviour is (as far as I remember) to

Hi All, I have a dataset, longitudinal in nature, each row is a 'visit' to a clinic, which has numerous data fields and a count variable for the number of 'events' that occurred since the previous visit. ~50k rows, ~2k unique subjects so ~25 rows/visits per subject, some have 50 some have 3 or 4. In STATA there is an adjustment for the fact that you have multiple rows per

On 02/12/2018 12:52 PM, Gerd Hoffmann wrote: > Hi, > >> can we reach agreement on whether vsock should be involved in this? > > I think the best approach would be to have guest proxy and host proxy > use vsock for the wayland protocol. Use a wayland protocol extension to > reference the buffers in stdvga / ivshmem / virtio-gpu. Only the two > proxies need to

On 02/12/2018 12:52 PM, Gerd Hoffmann wrote: > Hi, > >> can we reach agreement on whether vsock should be involved in this? > > I think the best approach would be to have guest proxy and host proxy > use vsock for the wayland protocol. Use a wayland protocol extension to > reference the buffers in stdvga / ivshmem / virtio-gpu. Only the two > proxies need to

The utils package has a misc folder, and some other packages have folders that are not listed in the R-extensions documentation (?data?, ? demo?, ?exec?, ?inst?, ?man?, ?po?, ?src?, and ?tests?). I'd like to be able to put some ancillary data into a misc folder, but it's mere presence in the source folder or source tarball (created with R CMD build) does not mean that it gets put into

I'm trying to replicate a time-series cross-sectional analysis (countries over years) with SEs clustered by country. ?The original analysis was done in Stata 10 with: xtreg [DV] [IVs] fe cluster(country). Using plm() in R (cran.r-project.org/web/packages/plm/index.html), I've replicated the coefficients. I sought to estimate country-clustered SEs with vcovHC(), and tried a variety of

Hello all, Tomas Bonnedahl and I recently corresponded about a rather odd behaviour with routes in ancillary routing tables. We both receive a "Network is unreachable" error when we try to add gatewayed routes to ancillary tables and the main routing table does not contain an entry for the gateway IP. It seems that unless a route to the gateway IP exists in the main routing table, I

CentOS 6.9 has support for the Haswell processor which is a subset of the Skylake. All Skylake server ancillary components work perfectly with CentOS 6.9. The AST2500 used with the Skylake is very good and will process UHD. However this is not backwards compatible with legacy variants. To make it work an ancillary graphics card is required which is less than $100. This will not break the

Hello, I am working with zero inflated models for a current project and I am getting wildly different results from R's zeroinfl(y ~ x, dist="negbin") command and Stata's zinb command. Does anyone know why this may be? I find it odd considering that zeroinfl(y ~ x, dist="poisson") gives identical to output to Stata's zip function. Thanks, --david [[alternative

On 02/12/2018 03:27 PM, Gerd Hoffmann wrote: > On Mon, Feb 12, 2018 at 03:00:24PM +0100, Tomeu Vizoso wrote: >> On 02/12/2018 12:52 PM, Gerd Hoffmann wrote: >>> Hi, >>> >>>> can we reach agreement on whether vsock should be involved in this? >>> >>> I think the best approach would be to have guest proxy and host proxy >>> use

Dear R-help, I was recently wanting to use GEE with the negative binomial "family". It seems that this is lacking in the otherwise excellent implementations of the GEE methodology ( packages: gee, yags, geepack). I would have thought it a simple step to allow the creation of a family, i.e providing the link function (log mu) and the variance function (mu + mu^2/theta) , assuming theta