similar to: negative predicted values in poisson glm

Dear all, I'm using zeroinfl() from the pscl-package for zero inflated Poisson regression. I would like to calculate (aproximate) prediction intervals for the fitted values. The package itself does not provide them. Can this be calculated analyticaly? Or do I have to use bootstrap? What I tried until now is to use bootstrap to estimate these intervals. Any comments on the code are welcome.

I have a question for users of MCMCglmm that have experience implementing the zero-inflated poisson model. I find that the documentation, and previous questions, do not offer a lot of clear guidance on specifying and interpreting the zipoisson model. In particular, I see a lot of zero-inflated poisson examples that use the at.level(trait, x):variableName syntax. Specifically, the MCMCglmm

Hi all-- I am in the process of helping colleagues write up a ms in which we fit zero-inflated Poisson models. I would prefer plotting the rate ratios and 95% CI (as I've found Gelman and others convincing about plotting tables...), but our journals usually like the numbers themselves. Thus, I'm looking at a recent JAMA article in which both numbers and dotplot of RR and 95% CI are

Are you referring to the zeroinfl() function in the countreg package? If so, I think predict(fm_zinb2, type = "zero", newdata = some.new.data) will give you pi for each combination of covariate values that you provide in some.new.data where pi is the probability to observe a zero from the point mass component. As to your second question, I'm not sure that's possible, for any

Hello ; I am doing a regression of count data (number of award and there are some covariates) I have estiamted the parameters of negative binomial distribuion (lambda is a function of covaraites, GLM model) by glm.nb function and training dataset. Now I want to predict the number of award (for example y=0, y=1, y=2,) or testing dataset. I dont know how to calculate this numbers? I would be very

Hi, I am trying to replicate Lambert (1992)'s simulation with zero-inflated Poisson models. The citation is here: @article{lambert1992zero, Author = {Lambert, D.}, Journal = {Technometrics}, Pages = {1--14}, Publisher = {JSTOR}, Title = {Zero-inflated {P}oisson regression, with an application to defects in manufacturing}, Year = {1992}} Specifically I am trying to recreate Table 2. But my

Good Day All, I have a negative binomial model which I have developed using the MASS library. I now would like to develop some predictions from it. Running the predict.glm (stats library) using type="response" gives me a non-integer value which was rather puzzling. I would like to confirm that this is actually the mean predicted value of the probability mass function as opposed

Hi, I am a little confused at the output from predict() for a zeroinfl object. Here's my confusion: ## From zeroinfl package fm_zinb2 <- zeroinfl(art ~ . | ., data = bioChemists, dist = "negbin") ## The raw zero-inflated overdispersed data > table(bioChemists$art) 0 1 2 3 4 5 6 7 8 9 10 11 12 16 19 275 246 178 84 67 27 17 12 1 2 1 1

I am running a zero inflated regression using the zeroinfl function similar to the model below: fm_zinb2 <- zeroinfl(art ~ . | ., data = bioChemists, dist = "poisson") summary(fm_zinb2) I have three questions: 1) How can I obtain a value for the parameter pie, which is the fraction of the population that is in the zero inflated model vs the fraction in the count model? 2) For

Dear all, I would like to know if there is a function for sorting a data.frame based on one column. sort() does it for a single vector but not for the whole data. order() does it if there are relations between the columns but in my case it is simply a data.frame. Further, I would like to plot other data, pop.size<- c(800, 800, 1500, 1000, 158, 300, 740, 250, 2000, 1500, 250, 700)

Hi, I've estimated a simple kernel density of a univariate variable with density(), but after I would like to find out the CDF at specific values. How can I do it? thanks for your help, with it I am very close to finish my first little bit more serious work in R, Viktor

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

R-users, My question is related to earlier posts about benefits of quadcore over dualcore computers; I am trying to setup a cluster of windows xp computers so that eventually I could make use of 10-20 cpu:s, but for learning how to do this, I am playing around with two laptops. I thought that the package snow would come handy in this situation, but to use snow, I would probably need to install

I have written the following function to calculate the weighted mean difference for univariate data (see http://www.xycoon.com/gini_mean_difference.htm for a related formula). Unsurprisingly, the function is slow (compared to sd or mad) for long vectors. I wonder if there's a way to make the function faster, short of creating an external C function. Thanks very much for your advice. gmd

I have compiled openssh for sun solaris 2.6, no errors When I try to run SSHD daemon it says the following error. This platform does not support both privilege separation and compression Compression disabled Privilege separation user sshd does not exist Any one that have answer to this problem mail me on daniel.d.olsson at telia.se <mailto:daniel.d.olsson at telia.se> //Daniel

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Caio Lucidius > Naberezny Azevedo > Sent: 01 September 2005 12:09 > To: Help mailing list - R > Subject: [R] Multivariate Skew Normal distribution > > > Hi all, > > Could anyone tell me if there is any package (or function)

Dear Asterisk Users, Are there any documentation that teach how to using Digium Cards to setup a PABX system? Thanks, Randal

In the document "R Data Import/Export", section "Output to connections", there is the following portion of code: ## convert decimal point to comma in output, using a pipe (Unix) zz <- pipe(paste("sed s/\\./,/ >", "outfile"), "w") cat(format(round(rnorm(100), 4)), sep = "\n", file = zz) close(zz) ## now look at the output

I have this problem with R 2.6.1 and 2.7.1 (have not tried others) running on Windows XP: Html help has wrong links to help files. The index.html is correctly found from file:///C:/PROGRA~1/R/R-26~1.1/doc/html/index.html as well as the search engine file:///C:/PROGRA~1/R/R-26~1.1/doc/html/search/SearchEngine.html However, when I search for, say, "paste", I will be pointed to

I have justed upgraded R v1.7.0 on Windows NT 4 and have installed the latest RMySQL (version 0.5-1)and DBI (version 0.1-5) packages. When I issue the following commands (tactfully adjusted) R just crashes and disappears, any ideas? require(RMySQL) m <- dbDriver("MySQL") con <- dbConnect(m, dbname="xxx", user="xxx", password="xxx",