similar to: negative multinomial regression models

Dear R-users, Is there an R function to compute the multinomial beta function? That is, the normalizing constant that arises in a Dirichlet distribution. For example, with three parameters the beta function is Beta(n1,n2,n2) = Gamma(n1)*Gamma(n2)*Gamma(n3)/Gamma(n1+n2+n3) Thanks in advance for any assisstance. Regards, Greg [[alternative HTML version deleted]]

lgamma(x) and lfactorial(x) are defined to return ln|Gamma(x)| {= log(abs(gamma(x)))} or ln|Gamma(x+1)| respectively. Unfortunately, we haven't chosen the analogous definition for lchoose(). So, currently > lchoose(1/2, 1:10) [1] -0.6931472 -2.0794415 NaN -3.2425924 NaN -3.8869494 [7] NaN -4.3357508 NaN -4.6805913 Warning message: In

hello, please can anyone help me out. Am a new user of R program. Am having problem with this code below, not getting the expected results. 1. Each m, the cumulative sum should be 1.000 but the 2nd and 3rd m returned 2.000 and 3.000 instead of 1.000. 2. to get the LCL(m) and UCL(m) for each m base on these instructions if out.cum > 0.025 then LCL(m)= y-1 if out.cum >0.975

hello, please can anyone help me out. Am a new user of R program. Am having problem with this code below, not getting the expected results. Each m, the cumulative sum should be 1.000 but the 2nd and 3rd m returned 2.000 and 3.000 instead of 1.000. thanks Aruike pp=function(x,n,M){z=1.0;a=2.3071430;b=7.266064;H=3 out.h=c() out.y=c() out.m=c() out.prob=c()

Hi, I would like to use the multinomRob function to test election results. However, depending on which independent variables I include and how many categories I have in the dependent variable, the model cannot be estimated. My data look like this (there are 68 observations): > head(database) RESTE09 GAUCHE09 PDC09 PLR09 UDC09 MCG09 RESTE05 GAUCHE05 PDC05 D1 1455

Dear: I try to revise the maximum likelihood function below using something constrains. But it seems something wrong with it. Becasue R would not allow me to edit the function like this. It is very appreciate if you can help. function (parameters,y,x1,x2) { p<-parameters[1] alpha1<-parameters[2] beta1<-parameters[3)] delta1<-parameters[4] alpha2<-parameters[5]

I am porting some FORTRAN to R in which an Inf triggers an if(). The trigger is infinite on exp(lgamma(OVER)). What is the canonical R style of determining OVER when exp(OVER)== Inf? The code structure that I am porting is best left intact--so I need to query R somehow to the value of OVER that causes exp(lgamma(OVER)) to equal Inf. On my system, exp(lgamma(171)) is about first to equal Inf.

Dear R users, i try to integrate lgamma from 0 to Inf. But here i get the message "roundoff error is detected in the extrapolation table", if i use 1.0e120 instead of Inf the computation works, but this is against the suggestion of integrates help information to use Inf explicitly. Using stirlings approximation doesnt bring the solution too. ## Stirlings approximation lgammaApprox

I've recently tried to get 0.62.3 up on our Suns (4.1.4, using gcc; I'm also having trouble with a Solaris 2.6 compile but I haven't given up hope on that one yet) -- the last compile I did was 0.61.1, which worked smoothly. Running ./configure --prefix=/usr/local/apps/R/R-0.62.3 [--with-g77] (tried both with and without g77, eventually get to the same place), I get a conflict

Hello R Help, I am trying solve an MLE convergence problem: I would like to estimate four parameters, p1, p2, mu1, mu2, which relate to the probabilities, P1, P2, P3, of a multinomial (trinomial) distribution. I am using the mle2() function and feeding it a time series dataset composed of four columns: time point, number of successes in category 1, number of successes in category 2, and

I am trying to solve the integration equation, for different values of K from 4 to 25, the integration is with respect to u, Here is the equation: gamma(k/2) / ( sqrt(k-1)*gamma((k-1)/2) ) * integrate(f= (1+u^2/k-1)^(-k/2), lower=0, upper= sqrt(a^2*k/(k+1-a^2)) ) = the similar expression as te left hand except k becomes k+1 my code is below, I don't know why R keep telling me the syntax

Hi, I found the following on Windows 2000/NT R Version 1.9.1 (2004-06-21) (also Version 1.9.0): The S4 group "Math" doesn't work as documented; i.e., "log", "log10", "gamma" and "lgamma" are included in the documentation but don't work. See example code below. Moreover, what about 'genericForPrimitive' which is used in

I'm a total newbie at using R, and so there probably is a better way to do this. However, I couldn't find one, and so maybe this will help someone. I was calculating log-likelihoods using a multinomial model, and found that for large n, prod(n:1) wouldn't work to calculate factorials (e.g., prod(200:1) = Inf). The below function calculates the natural log of a factorial (e.g.

Dear: Continuing the issue of 'ifelse'! I selecting the data whose 'x2'=1 for maximizing likelihood. I used two way to do this but the results are different. 1.Way one I use the data for x2=1 and run the program. It works for me. Tthe program is described as below: function (parameters,y1,x11) { p<-parameters[1] alpha1<-parameters[2] beta1<-parameters[3]

Hello, I submitted a package which used Fortran functions isnan and lgamma. However, I was told that: isnan and lgamma are not Fortran 95 functions. I was asked to write 'cross-platform portable code' and so should not be writing GNU extensions to Fortran. See http://cran.r-project.org/web/checks/check_results_mpath.html, which will shortly show installation failures under Solaris. I

Dear R users, I have two n*1 integer vectors, y1 and y2, where n is very very large. I'd like to compute elbp = 4^(y1) * 5^(y2) * sum_{i=0}^{max(y1, y2)} [{ (y1-i)! * (i)! * (y2-i)! }^(-1)]; that is, I need to compute "elbp" for each (y1, y2) pair. So I made R code like below, but I don't think it's efficient Would you plz tell me how to avoid this "for"

Dear R-Help, I'm hoping to find a Multinomial Nested Logit package in R. It would be great to find something analogous to "PROC MDC" in SAS: > The MDC (Multinomial Discrete Choice) procedure analyzes models > where the > choice set consists of multiple alternatives. This procedure > supports conditional logit, > mixed logit, heteroscedastic extreme value,

Dear Sirs, Could you please be so kind as to send us some information on residuals in multinomial logistic models? Is it possible to use R software? We thank you in advance. Sincerely yours Luciana Alves,MSc Beatriz Leimann, MD -- Luciana Correia Alves Doutoranda em Sa??de P??blica ENSP - Fiocruz

Dear R users: I wonder anyone is aware of such a thing from lgamma() > lgamma(-0.8) [1] 1.747207 I thought it should be NA as in S-PLUS. Both R-1.3.1 and R-1.5.1 report this result. I don't have the latest R-1.6.1 so I don't know whether this is corrected or not. Happy holidays, Paul.

Hi All, What is the R function for computing multinomial distribution, e.g. f(2,1,3; 2/9, 1/6, 11/18, 6)? That is, a total of 6 trials, event 1's p1=2/9, x1=2, event 2's p2=1/6, x2=1, and event 3's p3=11/18, x3=3. thanks, Johnny [[alternative HTML version deleted]]