similar to: Goodness of fit to Poisson / NegBinomial

This came up on r-help but indicates a bug. dnbinom(x,n,p) calls dbinom_raw(n-1,...) which returns 0 for n<1. -thomas ---------- Forwarded message ---------- Date: Thu, 08 Feb 2001 17:10:23 +0000 From: Yudi Pawitan <yudi@stat.ucc.ie> To: Mark Myatt <mark@myatt.demon.co.uk> Cc: R-Help <r-help@stat.math.ethz.ch> Subject: Re: [R] Goodness of fit to Poisson / NegBinomial

I know that my question is like a very newbie question, but at the moment I stacked with it and I need a quick solution. I need to make an overall statistical overview of various datasets, the summary() and numSummary() functions are fully sufficient. My question is, how can I export results to a spreadsheet-like file, as a .csv. For the summary() with an "x" dataset I can use this way:

Try changing your method to "ML" and try again. I tried the run the first example from the documentation and it failed with the same error. Changing the estimation method to ML worked. @List: Can anyone else verify the error I got? I literally ran the following two lines interactively from the example for goodfit: dummy <- rnbinom(200, size = 1.5, prob = 0.8) gf <- goodfit(dummy,

Dear R-help gurus (and T.Yee, the VGAM maintainer) - I've been banging my head against the keyboard for too long now, hopefully someone can pick up on the errors of my ways... I am trying to use optim to fit a zero-inflated negative binomial distribution. No matter what I try I can't get optim to recognize my initial parameters. I think the problem is that dnbinom allows either

Hi every body: I need some help with kendall.global. The example in the manual seems not working well, and cannot used with my data, always the same error. data(mite) > mite.hel <- decostand(mite, "hel") > > # Reproduce the results shown in Table 2 of Legendre (2005), a single group > mite.small <- mite.hel[c(4,9,14,22,31,34,45,53,61,69),c(13:15,23)] >

Hi folks, I am having a weird problem that I just recently noticed on this particular server runnng Samba 3.0.10 on Fedora Core 3 and am hoping someone could shed some light on this. We're using tdb for our backend database. The user "nsu" is a member of unix group admin. The unix group admin is mapped to "Domain Adminstrators". This works OK, in that when logging in

I am running a binomial glm with response variable the no of mites of two species y->cbind(mitea,miteb) against two continuous variables (temperature and predatory mites) - see below. My model shows overdispersion as the residual deviance is 48.81 on 5 degrees of freedom. If I use quasibinomial to account for overdispersion the dispersion parameter estimate is 2501139, which seems

Dear all i?m working with a program i?ve made in R (using functions that others created) to run my program i need a sample. if i generate the sample using for example, rnorm(n, mu, sigma) i have no problem but if i obtain a sample from a column in excel and i copy it, the program says that there is a mistake: it says "Error en `[.data.frame`(data, indices) : undefined columns

I read a table as follows: > F1 <- read.table("Rtext3.txt") > F1 Price Floor Area Rooms Age Cent.heat a 52.00 111 830 5 6.2 no b 54.75 128 710 5 7.5 no c 57.50 101 1000 5 4.2 no d 57.50 131 690 6 8.8 no e 59.75 93 900 5 1.9 yes As it is seen, the rows have a name. However I don't know how to access a

I'm having some difficulty with graphing outputs of a GLM model I've been working. I have count data for both my predictor (only 1) and response variables, and I have pseudoreplication which I've modeled as a random effect. The odTest() from pscl:: indicated that the negative binomial distribution fit better than Poisson, and I then proceeded by estimating theta from glm.nb. My

Dear Experts, Probably trivial, but I am struggling to get what I want: I need to know how the number of required trials to get a certain number of successes. By example: How many trials do I need to have 98% probability of 50 successes, when the a priory probability is 0.1 per trial. The Negative binomial function may do the job (not sure): NegBinomial {stats} The Negative Binomial

Hi there, I switched servers yesterday. The old server was running 2.2.7a-1 on RedHat 8.0. The new server is 3.0.8-0.pre1.3 on Fedora Core 3. I did the migration by copying the following: /etc/passwd /etc/group /etc/shadow /etc/samba/* I then copied /home and fixed all the permissions on stuff. I then started up samba on the new server, and unplugged the old one. Most everything went

There is a problem with `rpois'. It does seem to take care about the order of the arguments. This is an example: > rpois(n=1,lambda=2) [1] 3 > rpois(lambda=2,n=1) [1] 2 0 It obviously uses the first argument as the number of samples to be drawn, which is wrong. I used Version 0.49 Beta (April 23, 1997). Fredrik

There is a problem with `rpois'. It does seem to take care about the order of the arguments. This is an example: > rpois(n=1,lambda=2) [1] 3 > rpois(lambda=2,n=1) [1] 2 0 It obviously uses the first argument as the number of samples to be drawn, which is wrong. I used Version 0.49 Beta (April 23, 1997). Fredrik

Hi, The code below is giving me this error message: Error in while (err > eps) { : missing value where TRUE/FALSE needed In addition: Warning messages: 1: In dnbinom(x, size, prob, log) : NaNs produced 2: In dnbinom(x, size, prob, log) : NaNs produced I know from the help files that for dnbinom "Invalid size or prob will result in return value NaN, with a warning", but I am not able

Full_Name: Andrey Pavlov Version: 2.7.1 (2008-06-23) OS: Windows Vista Submission from: (NULL) (67.193.233.43) Dear developers, I discovered an issue with the dnbinom function while fitting a negative binomial model to my data. I was using the size and mu parameterization. When the size gets large enough, the function begins to return 1, while it should instead return the respective Poisson

Dear colleague, I not sure this R code is correctly ? I would to show the number of Sample Size at Sample Size Axis that line draw from Power Axis (80%) from R code. How I show this and select the most appropriate of this power (.79955687 - 80983575). Thank for your help and answer. Best Regards, Nikom Thanomsieng, Email: nikom at kku.ac.th .... #Power analysis: Sample size for

Dear list, I would like to fit a negative binomial regression model as described in "Byers AL, Allore H, Gill TM, Peduzzi PN., Application of negative binomial modeling for discrete outcomes: a case study in aging research. J Clin Epidemiol. 2003 Jun;56(6):559-64" to my data in which the response is count data. There are also 10 predictors that are count data, and I have also 3

Dear R users I have built several glmm models using glmmPQL in the following structure: m1<-glmmPQL(dev~env*har*treat+dens, random = ~1|pop/rep, family = Gamma) (full script below, data attached) I have tried all the methods I can find to obtain some sort of model fit score or to compare between models using following the deletion of terms (i.e. AIC, logLik, anova.lme(m1,m2)), but I

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 ~ turns out I don't need to look at the C code. ~ if one uses the mu/size parameterization of the negative binomial, R computes size/(size+mu) to switch parameterizations. If size>>mu this gets rounded to 1 ... should be easy enough to test and return NA under these circumstances? function (x, size, prob, mu, log = FALSE) { ~ if