similar to: How to do poisson distribution test like this?

Dear Sir/Madam, I apologize for any cross-posting. I got a simple question, which I thought the R list may help me to find an answer. Suppose we have Y_1, Y_2, ., Y_n ~ Poisson (Lambda_i) and Lambda_i ~Gamma(alpha_i, beta_i). Empirical Bayes Estimator for hyper-parameters of the gamma distr, i.e. (alpha_t, beta_t) are needed. y=c(12,5,17,14) n=4 What about a Hierarchal B ayes

Please help, I tried a program on S-plus, and it worked. Also I tried the same program on R but not worked. Here is the programme. I put it in a function form. The model and assumption are at the bottom. where counts<-c(22,2,2,0,5,7,14,0,0,2,36,0,0,1,17,10) which is name.data, i is row size and j is the column size. symmetry function(i, j, name.data) { row <- (c(1:i)) col <-

Thank you so much Rui. 1. How do I export this table to excel file? I used this tbl1 <- table(Country, IDNum) tbl2=addmargins(tbl1) write.xlsx(tbl2,"tt1.xlsx"),sheetName="summary", row.names=FALSE) The above did not give me that table. 2. I want select those unique Ids that do have records in all countries. From the above data set, this ID

Assume that we collect below data : - subjects = 20 males + 20 females, every single individual is independence, and difference events = 1, 2, 3... n covariates = 4 blood types A, B, AB, O http://r.789695.n4.nabble.com/file/n4245397/CodeCogsEqn.jpeg ?m = hazards rates for male ?n = hazards rates for female Wm = Wn x ?, frailty for males, where ? is the edge ratio of male compare to female Wn =

Dear Listers, I have a general statistical question. Are hurdle logit-poisson model and posson model nested? Thank you so much?

Hi All, I have a sequence of positive integers, which is right skewed. The mean value is 6 and variance is 11. I suspect it can be fitted by poisson distribution. But I'm not familiar with the function to fit distribution. Could you please help me with it? Also, once I fit the poisson distribution, how can I check the good-ness of this fitting? Thank you! [[alternative HTML

Dear All I would like to know whether it is possible with R to generate random numbers from zero-truncated Poisson distribution. Thanks in advance, Galina

Hello, from a search of the archives and functions, I am looking for information on creating random correlated counts from a multivariate Poisson distribution.  I can not seem to find a function that does this. Perhaps, it has not yet  been created. Has anyone created an R package that does this.   thanks,   Jourdan Gold     [[alternative HTML version deleted]]

Hi all, I have a data set need to be summarized by unique ID (count and sum of a variable) A unique individual ID (country name Abbreviation followed by an integer numbers) may have observation in several countries. Then the ID was changed by adding the country code as a prefix and new ID was constructed or recorded like (country code, + the original unique ID Example original ID

Hello forum, I want to do a test of independence with svychisq, but I get an error, then this my code: am18 <- read.spss("C:/Users/diana/Dropbox/Semestre 10/Tesis 10/Tesis Diana/AMcomuna18-29MAR2012.sav", use.value.labels=TRUE, max.value.labels=Inf, to.data.frame=TRUE) b<-matrix(c(am18$N6_MANZANA),ncol=1) c<-matrix(c(am18$PM1_1_PONDEMUESTRA),ncol=1)

This is a basics beginner question. I attempted fitting a a Poisson GLM to data that is non-integer ( I believe Poisson is suitable in this case, because it is modelling counts of infections, but the data collected are all non-negative numbers with 2 decimal places). My question is, since R doesn't return an error with this glm fitting, is it important that the data is non-integer. How does

Hi I am trying to carry out some maximum likelihood estimation and I'm not making much headway, and I'm hoping that someone will be able to point me in the right direction. I am modelling mortality statistics. One way to do this is to model the mortality rate (or, more accurately, log of the mortality rate, log_m) as (say) a constant plus a proportion of age, plus time, so: r_1 <-

I would like to test in R what regression fits my data best. My dependent variable is a count, and has a lot of zeros. And I would need some help to determine what model and family to use (poisson or quasipoisson, or zero-inflated poisson regression), and how to test the assumptions. 1) Poisson Regression: as far as I understand, the strong assumption is that dependent variable mean = variance.

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

Hi -I'm running a GAM with 7 explanatory variables with a Poisson error structure. All of the variables are continuous so I'm getting error messages in R. cod.fall.full.gam.model<-gam(Kept.CPUE~s(HOUR)+s(LAT_dec)+s(LONG_dec)+s(meantemp_C)+s(meandepth_fa)+s(change_depth)+s(seds), data=cod.fall.version2,family=poisson) In dpois(y, mu, log = TRUE) ... : non-integer x = 5.325517

Dear sir, I want to know about R command for parameter estimation for generalized Poisson regression. yours faithfully Arafat Ud Zaman 4th year(Hons) Applied statistics University of Dhaka Mob- +8801715173176 E-mail: arafat.zaman@yahoo.com azaman1@isrt.ac.bd azaman1@quantummethod.org.bd [[alternative HTML version deleted]]

Dear everyone I'm dealing with a problem related to Poisson Ridge Regression. If anyone can help me in this regard by telling if any changes in the source code of "glm.fit" may help -- Regards Umesh Khatri

Dear R helpers, running the following code of a glm model of the family poisson, gives predicted values < 0. Why? library(MASS) library(stats) library(mvtnorm) library(pscl) data(bioChemists) poisson_glm <- glm(art ~ fem + mar + kid5 + phd + ment, data = bioChemists, family = poisson) predicted.values = predict(poisson_glm) range(predicted.values) Thank you in advance for any hints.

Hi all, I would like to estimate power and necessary sample size for a GLM with a response variable that has a poisson distribution. Do you have any suggestions for how I can do this in R? Thank you for your help. Sincerely, Craig -- Craig A. Faulhaber Department of Forest, Range, and Wildlife Sciences Utah State University 5230 Old Main Hill Logan, UT 84322 (435)797-3892

Dear all, I have a very basic question: how does the logLik function work for poisson models? Example: I simulate 20 observations from a Poisson distribution with mean 800. y <- rpois(20,800) model <- glm(y ~ 1, family=poisson()) logLik(model) I would like to know what's the exact formula the function logLik uses. I looked at ?extractAIC but I cannot sort it out. Can you please