similar to: Quasi-Binomial simulation

Does anyone have R functions or library to fit a beta-binomial distribution with glm? Thanks.

I am using curve3d in the emdbook package to graph a gaussian copula density function generated via the copula package. Unfortunately, it appears that emdbook masks dmvnorm from the package mvtnorm in a way that prohibits copula from generating the gaussian copula. (Sounds very confusing!) For example, > library(copula) > f<-function(x,y) dcopula(normalCopula(0),c(x,y)) >

the version 2 parser thinks I have unnecessary braces, but I can't find any. False positive or am I missing something? If a false positive, is there any way to work around the warning? * checking Rd files against version 2 parser ... WARNING Warning: ./man/dbetabinom.Rd:32-34: Unnecessary braces at ?{p(x) = % (C(N,x)*Beta(N-x+theta*(1-p),x+theta*p))/% Beta(theta*(1-p),theta*p)}?

When I submit more than one batch file (same programs, different parameter values, huge simulations, different result names) the only results that get saved are from the *last* batch file to finish. They are all being run in the same subdirectory (so same .RData file?) I've done: R --save BATCH infile outfile and I've also put q(save="yes") at the end of the program, but

Hello, I am using rbetabinom ( to generate beta binomial random variables) function available in the "emdbook"package written by Professor. Ben Bolker for my research study. I have no questions with this function. However, I am looking for the theoretical method/algorithm of the function "rbetabinom " . Morris (1997), American Naturalist 150:299-327 is given as the reference

I have recently "printed" in R to a postscript file. I'm working on a SSH without an X terminal. It was fairly automatic: > plot(x,y) > dev.off() And then the default creates a file called Rplots.ps which I can ftp to my laptop and open in Ghostscript. I can see the file, and nothing looks odd. However, when I import it into LaTeX, it refuses to configure right side up.

If I want to find out the soltion of X1,X2 that min(3X1+2X2+X1X2) subject to 20<=X1+3X2<=50 10<=X1 which function or package can I use? Thanks.

Did the MASS package disappear? Specifically, I'm looking for a function to find the MCD (robust measure of shape and location) for a multi-dimensional data matrix. Anyone know anything about this? Thanks, Jo Jo Hardin Assistant Professor Department of Mathematics Pomona College 610 N. College Ave. Claremont, CA 91711 909-607-8717 jo.hardin@pomona.edu [[alternative

Hi, I'm using a GLM with a quasi binomial error distribution and I would like to do a model selection method similar to step(AIC) to carry out a restricted search for the "best" model. I would like to know which of my 5 predictor variables would be included in the "best" model if I start with a 'full' model (fullbinom in this case). However, AIC can't be

Hello, Has anyone written up code to estimate for example a simple logit using quasi-likelihood? I know that glm() already does this, but I'd like to do some tinkering with the variance function beyond what glm() allows. I've scanned online sources and everyone seems to use glm(). Will take a crack at it if necessary but have zero experience w/q-likelihood and not that much with

Hi all, I have run a (glm) analysis where the dependent variable is the gender (family=binomial) and the predictors are percentages. I get a warning saying "fitted probabilities numerically 0 or 1 occurred" that is indicating that quasi-separation or separation is occurring. This makes sense given that one of these predictors have a very influential effect that is depending on a

Dear R-helpers, this mail is intended to mention a rather trange result and generate potential useful comments on it. I am not aware of another posts on this issue ( RSiteSearch("quasipoisson lmer version dispersion")). MUsing the exemple in the reference of the lmer function (in lme4 library) and turning it into a quasi-poisson or quasi-binomial analysis, we get different results,

On Jul 24, 2013 2:52 AM, "Jacob Carlborg" <doob at me.com> wrote: > > Do your LLVM development on Mac OS X :) Should work well. Apple is one of the bigger supporters of LLVM, so I'd hope OS X would be a suitable dev platform. > It depends on what your needs are. Using VirtualBox will probably be the easiest. It also allows you to run both Mac OS X and Ubuntu

Are there any R packages that could be used to generate random data given a set of parameters? Or, if not a package, how would one generate such data? What I would like to do is simulate some sample data for a regression model given a set of population covariances and distribution parameters to be used in a MC simulation. Thanks for any tips. [[alternative HTML version deleted]]

Dear all, I want to use the deltavar() function from emdbook. I can use it directly from the command terminal but within a function it behaves weird. Working example: ---------------------- library("emdbook") fn <- function() { browser() y <- 2 print(deltavar(y*b2, meanval=c(b2=3), Sigma=1) ) } x <- 2 print(deltavar(x*b1, meanval=c(b1=3), Sigma=1) ) y<-3 fn()

Hi, LLVM made a change a few months ago and starting erroring out when a float is returned in x64 and SSE is disabled. This makes sense, really, since it's specified by the ABI that the return value must be put in a register you were told to disable, but it's breaking soft floats in Rust on x64. It seems there are two options: LLVM could break the ABI spec and have working soft floats on

I have data that looks like O.lengthO.age 176 1 179 1 182 1 ... 493 5 494 5 514 5 606 5 462 6 491 6 537 6 553 6 432 7 522 7 625 8 661 8 687 10 704 10 615 12 (truncated) with a simple VonB growth model from within nls(): plot(O.length~O.age, data=OS) Oto = nls(O.length~Linf*(1-exp(-k*(O.age-t0))), data=OS, start=list(Linf=1000, k=0.1, t0=0.1), trace=TRUE) mod <- seq(0, 12)

Hi, all. I know that this is probably something that others have asked, but I can't find a reference in either the FAQ or the help pages. I'm trying to find a way to put Greek letters as a label of the plot *with* a value from the data. Previously I've used pasted and the word "rho". * paste("rho=", cor2[i]) will produce a label of

Dear All, I am analysing a dataset on levels of herbivory in seedlings in an experimental setup in a rainforest. I have seven classes/categories of seedling damage/herbivory that I want to analyse, modelling each separately. There are twenty maternal trees, with eight groups of seedlings around each. Each tree has a TreeID, which I use as the random effect (blocking factor). There are two

So it turns out that I was wrong. It, in fact, is not standard. But regardless, you can use asm to specify the exact name. Eg. extern int func() asm("func"); You can read more here: http://stackoverflow.com/questions/1034852/adding-leading-underscores-to-assembly-symbols-with-gcc-on-win32 Despite the title of the thread, the solution is compiler and system independent. --------------