search for: dnbinom

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 to find a workaround for this in my code to avoid it. I appreciate t...

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 probability. This can be seen in the following simple example: > dpo...

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: [...

...be easy enough to test and return NA under these circumstances? function (x, size, prob, mu, log = FALSE) { ~ if (!missing(mu)) { ~ if (!missing(prob)) ~ stop("'prob' and 'mu' both specified") ~ prob <- size/(size + mu) ~ } ~ .Internal(dnbinom(x, size, prob, log)) } ~ Ben Bolker - -------------------------- ~ Check it out: curve(dnbinom(1,mu=0.5,size=x),log="x",from=1,to=1e18) abline(h=dpois(1,lambda=0.5),col=2,lty=2) text(1,dpois(1,lambda=0.5)+0.02,"Poisson",col=2,pos=4) ~ I will take a look in the C code whe...

...nging 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 'prob' or 'mu' and I am trying to pass it 'mu'. I've tried a wrapper function but it still hangs. An example: #set up dummy data,load VGAM, which is where I am getting the zero-inflated neg binom #I get the same problem without VGAM, using dnbinom in the...

my current code for dnbinom.c has prob = dbinom_raw(n,x+n,p,1-p,give_log); f = ((double)n)/((double)(n+x)); return((give_log) ? log(f) + prob : f*prob); which should work for x>=0, n>=0, 0<=p<=1. dbinom.raw(x,n,p) is intended to work for x>=0, n>=0, 0<=p<=1, without integer checks. When necessar...

...nteractions, when I try to evaluate two pairs of interactions( flowers*gopher, flowers*rockiness) my computer runs out of memory, and the larger desktop I use just doesn't go anywhere after about 20 minutes. Is it really that big a calculation? to start: mle2(minuslogl = Lily_sum$seedlings ~ dnbinom(mu = a, size = k), start = list(a = 10, k = 1)) then: i2<-interaction(Lily_sum$flowers, Lily_sum$gopher) i3<-interaction(Lily_sum$flowers, Lily_sum$rockiness) mle2(Lily_sum$seedlings ~ dnbinom(mu = a, size = k), start=list(a=10,k=1) ,parameters=list(a~i3+i2+Lily_sum$flowers)) (the last ru...

...ing the number of particles. I first fit a negative binomial model using > nbFit<-glmer.nb(Count ~ Cleaning + (1|Sampling_point) , data = myCountDB) I now would like to add a curve to the histogram representing the negative binomial density function fitted to my data using > curve(dnbinom(x=, size=, prob=, mu=), add=TRUE) But I am struggling defining the arguments to dnbinom. Using the str() function on the nbFit object I see there are many fields returned. And I get lost reading the ?glmer.nb help, greatly because of my lack of knowledge. Which ones should I use? Thanks ever...

...rsion 2.9.0 Under development (unstable) (2008-12-03 r47039) i386-pc-mingw32 Thanks a lot Thomas Petzoldt set.seed(3577) # make it reproducible ## 1) example taken from ?nlminb ------------------------------------- x <- rnbinom(100, mu = 10, size = 10) hdev <- function(par) { -sum(dnbinom(x, mu = par[1], size = par[2], log = TRUE)) } nlminb(c(20, 20), hdev, lower = 0.001, upper = Inf) ## --> works without problems ## 2) same example, but with named vectors ----------------------------- hdev <- function(par) { cat(names(par), "\n") # show what happens -sum...

Dear Ben, you answerd to Nancy Shackelford about Clarks 2Dt function. Since the thread ended just after your reply, I would like to ask, if you have an idea how to use this function in R I defined it the following way: function(x , p, u) { (p/(pi*u))*(1+(x^2/u))^(p+1) } and would like to fit this one to my obeservational data (count) [,1] [,2] [1,] 15 12 [2,] 45 13 [3,]

...ative binomial model using > > >> nbFit<-glmer.nb(Count ~ Cleaning + (1|Sampling_point) , data = myCountDB) > > > > I now would like to add a curve to the histogram representing the negative binomial density function fitted to my data using > > >> curve(dnbinom(x=, size=, prob=, mu=), add=TRUE) Why not use the predict function in that package? See ?merMod -- David. > > > But I am struggling defining the arguments to dnbinom. > > > Using the str() function on the nbFit object I see there are many fields returned. And I get lost re...

All, I have some data on parasites on apple leaves and want to do a goodness of fit test to a Poisson distribution. This seems to do it: mites <- c(rep(0,70), rep(1,38), rep(2,17), rep(3,10), rep(4,9), rep(5,3), rep(6,2), rep(7,1)) tab <- table(mites) NSU <- length(mites) N <-

...e: x86 release: NT 5.0 R.Version() tells me: platform: i386-pc-mingw32 arch: i386 os: mingw32 system: i386, mingw32 status: R.version.string: R version 1.6.2, 2003-01-10 My full code is here: dnegbinp <- function(x,prob,mu,size,log=FALSE) { ll <- ifelse(x==0, log(1-prob+prob*dnbinom(0*x,mu=mu,size=size)), log(prob)+dnbinom(x,mu=mu,size=size,log=TRUE)); if (log) ll else exp(ll); } x <- c(1,3,0,19,32,0,0,2,23,23) loglikfun <- function(p) { cat("Eval fn at ") cat(p) s <- -sum(dnegbinp(x, prob=p[[1]],mu=p[[2]],size=p[[3]], log=TRUE))...

...t a negative binomial model using > > >> nbFit<-glmer.nb(Count ~ Cleaning + (1|Sampling_point) , data = myCountDB) > > > > I now would like to add a curve to the histogram representing the negative binomial density function fitted to my data using > > >> curve(dnbinom(x=, size=, prob=, mu=), add=TRUE) Why not use the predict function in that package? See ?merMod -- David. > > > But I am struggling defining the arguments to dnbinom. > > > Using the str() function on the nbFit object I see there are many fields returned. And I get lost reading...

Hey, So I have a scatter plot and I am trying to plot a curve to fit the data based on a Holling Type III functional response. My function is this: nll2<-function(a,b) { conefun<-(a*DBH^2)/(b^2+DBH^2) nlls2<-dnbinom(x=cones ,size=DBH, mu=conefun,log=TRUE) -sum(nlls) } and my plot is this: plot (DBH,cones) DBH is on the x-axis and cones is on the y-axis. How do I get the curve for my function onto the scatterplot? -- View this message in context: http://r.789695.n4.nabble.com/Plotting-a-curve-for-a-Hol...

Hello I want to use the nlminb function but I have the objective function like characters. I can summarize the problem using the first example in the nlminb documentation. x <- rnbinom(100, mu = 10, size = 10) hdev <- function(par) -sum(dnbinom(x, mu = par[1], size = par[2], log = TRUE)) nlminb(c(9, 12), objective=hdev) With the last instructions we obtain appropriate results. If I have the name of the objective function stored in the element name, how can modify the next two instructions to obtain the same above results? name <- ...

...es")= chr "lambda" $ sd : Named num 0.213 ..- attr(*, "names")= chr "lambda" $ n : int 337 $ loglik : num -2721 - attr(*, "class")= chr "fitdistr" > nb15 = fitdistr(x15,"negative binomial") Warning messages: 1: In dnbinom(x, size, prob, log) : NaNs produced 2: In dnbinom(x, size, prob, log) : NaNs produced 3: In dnbinom(x, size, prob, log) : NaNs produced > str(nb15) List of 4 $ estimate: Named num [1:2] 0.973 15.309 ..- attr(*, "names")= chr [1:2] "size" "mu" $ sd : Named...

...i386-apple-darwin8.10.1 locale: zh_CN.UTF-8/zh_CN.UTF-8/C/C/zh_CN.UTF-8/zh_CN.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] mclust_3.1-5 x <- rnbinom(100, mu = 10, size = 10) hdev <- function(par) { -sum(dnbinom(x, mu = par[1], size = par[2], log = TRUE)) } nlminb(c(9, 12), hdev) ----------------------------------------------- Peng Jiang 江鹏 ,Ph.D. Candidate Antai College of Economics & Management 安泰经济管理学院 Department of Mathematics 数学系 Shanghai Jiaotong University (Minhang Campus) 800 Dongchuan Road 200...

Full_Name: Chanseok Park Version: R 2.2.1 OS: RedHat EL4 Submission from: (NULL) (130.127.112.89) pbinom(any negative value, size, prob) should be zero. But I got the following results. I mean, if a negative value is close to zero, then pbinom() calculate pbinom(0, size, prob). dbinom() also behaves similarly. > pbinom( -2.220446e-22, 3,.1) [1] 0.729 > pbinom( -2.220446e-8, 3,.1)

...erpad_max_install_names -mmacosx-version-min=10.4 -undefined dynamic_lookup -single_module -multiply_defined suppress -L/usr/local/ lib -o pnmath.so bd0.o beta.o chebyshev.o choose.o d1mach.o dbeta.o dbinom.o dcauchy.o dchisq.o dexp.o df.o dgamma.o dgeom.o dhyper.o dlnorm.o dlogis.o dnbeta.o dnbinom.o dnchisq.o dnf.o dnorm.o dnt.o dpois.o dt.o dunif.o dweibull.o fmax2.o fmin2.o ftrunc.o gamma.o gamma_cody.o i1mach.o imax2.o imin2.o lbeta.o lgamma.o lgammacor.o mlutils.o pbeta.o pbinom.o pcauchy.o pchisq.o pexp.o pf.o pgamma.o pgeom.o phyper.o plnorm.o plogis.o pnbeta.o pnbinom.o pnchis...