similar to: OPTIM--non finite finite different [13]

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]

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]

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

Dear All: I tried to fit negative binomial distribution to data in terms of mean and mean is also a quadratic function of another variable. The likelihood function is: function (parameters, y1,x11) { p<-parameters[1] alpha1<-parameters[1] beta1<-parameters[2] delta1<-parameters[3] mu<-alpha1+beta1*(x11)+delta1*(x11^2) ifelse(y1>=0|x11>=0, L<-

Hello all, I was going to solve (n-m)! * (n-k)! = 0.5 *n! * (n-m-k)! for m when values of n and k are provided n1<-c(10,13,18,30,60,100,500)         # values of n kx<-seq(1,7,1);                               # values of k slv2<-lapply(n1,function(n){    slv1<-lapply(kx,function(k){              lhs<-function(m)              {                

Version 1.3.1 (2001-08-31) factorial() is not in R. It is in S-Plus with the definition factorial <- function(n) gamma(n + 1) -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not

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

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

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

Hello, I''ve spent a lot of time during the past month trying to get negative multinomial regression models for clustered event counts as described in (Guang Guo. 1996. "Negative Multinomial Regression Models For Clustered Event Counts." Sociological Methodology 26: 113-132., abstract at http://depts.washington.edu/socmeth2/4abst96.htm) implemented in R. A FORTRAN version of the

I have some big combinations like: 4444444444444444444444444444 choose 784645433 Can R compute these? Is there any package that does stirlings approximation in R? -- Thanks, Jim. [[alternative HTML version deleted]]

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

I am working on a project that requires me to do very large factorial evaluations. On R the built in factorial function and the one I created both are not able to do factorials over 170. The first gives an error and mine return Inf. Is there a way to have R do these larger calculations (the calculator in accessories can do 10000 factorial and Maple can do even larger) -- View this message in

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 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.