similar to: ties in runif() output

I have been trying to use the rbeta() function to generate random beta variates with a particular mean and standard deviaiton for some simulation problems I am working on, however I am unsure of the relationship between the parameters shape1 and shape2 and the mean and standard deviation of the beta distribution. I am guessing that there is a formula for this, but I am unsure what it is. Can

Hi!!! It would like to know if it exists a form to use the functions to generate variates in FORTRAN with the same easiness I use that them in C? Or not? If yes. They would have some example? I would like to use the functions rbeta, rlnorm and others! Sorry my english..rsrsrs Thanks!!!              Fábio Mathias Corrêa    University Federal of the Lavras - Brazil Veja quais são os

Hi folks, I have a question about how to efficiently produce random numbers from Beta and Binomial distributions. For Beta distribution, suppose we have two shape vectors shape1 and shape2. I hope to generate a 10000 x 2 matrix X whose i th rwo is a sample from reta(2,shape1[i]mshape2[i]). Of course this can be done via loops: for(i in 1:10000) { X[i,]=rbeta(2,shape1[i],shape2[i]) } However,

Dear R users: I was trying to fit a HMM with mixture of Gaussian into the dataset, and I tried to implement it by R2Winbugs. But I got the following errer. * Error in FUN(X[[1L]], ...) : .C(..): 'type' must be "real" for this format* Does anybody know what's the problem? Does R2Winbugs accept some matrix as inits? I would really appreciate your help. Thank you very much.

On a recent FreeBSD 8.0-CURRENT (i386) building R (any version) breaks with the following messages: ---------------------------------------------------------------------- [...snip...] gcc -std=gnu99 -I. -I../../src/include -I../../src/include -I/usr/local/include -DHAVE_CONFIG_H -g -O2 -c wilcox.c -o wilcox.o gcc -std=gnu99 -I. -I../../src/include -I../../src/include -I/usr/local/include

I installed R 0.64.2 using "rwinst.exe" on a Windows 95 machine. The zip files and rwinst.exe were stored in a directory "rtmp" and I wanted R to be installed in "r0642" (by setting c:\rtmp for source directory and c:\ for install directory). After the installation was completed the main program was in r0642 whereas all the documentation in c:\rtmp\r0642. Is this

Hi, in the code below, I am drawing 1000 samples from two beta distributions, each time using the same random number seed. Using set.seed(80) produces results I expect, in that the differences between the distributions are very small. Using set.seed(20) produces results I can't make sense of. Around half of the time, it behaves as with set.seed(80), but around half of the time, it behaves

I have the following problem: I have a vector x of data (0<x<=1 ) with a U-shaped histogram and try to fit a beta distribution using fitdistr. In fact, hist(rbeta(100,0.1,0.1)) looks a lot like my data. The equivalent to the example in the manual sometimes work: > a <- rbeta(100,0.1,0.1) > fitdistr(x=a, "beta", start=list(shape1=0.1,shape2=0.1))1) > shape1

Hi R users: I try this code, where "fun" is a parameter of a random generating function name, and I pretend to use "..." parameter to pass the parameters of different random generating functions. What am I doing wrong? f1<-function(nsim=20,n=10,fun=rnorm,...){ vp<-replicate(nsim,t.test(fun(n,...),fun(n,...))$p.value) return(vp) } This works! f1()

Hi R users: I'm trying to make a function where two of the parameters are functions, but I don't know how to put each set of parameters for each function. What am I missing? I try this code: f2<-function(n=2,nsim=100,fun1=rnorm,par1=list(),fun2=rnorm,par2=list()){ force(fun1) force(fun2) force(n) p1<-unlist(par1) p2<-unlist(par2) force(p1) force(p2)

Hi everyone, I have built an R package and for the sake of speed I have decided to rewrite some part of the code in C++. In my original R code I use the pnorm, qnorm, rnorm, pgamma, dgamma, rgamma, rbeta and runif function. First I was thinking in going with the boost libraries, but I noticed the functions described above are available within the R.h header file (or is it Rmath.h?). So my

Hi All, I am new to this area and use Rcpp to call C++ from R and try to build the package under Windows 7. I use Rtools and R 2.10.1 32bit. Everything works fine with me, except using R functions like "rnorm" or "runif" in the C++ code. When I use "R CMD check" the package, it always return error ** libs making DLL ... g++

Dear R helpers, I have some difficulties in using ''break'' function with loop, and the followings are my script. What I try to do is (1) permute ''or'' first; (2) doing t-test if this ''or'' pass criteria 1 (k=1); (3) end the loop when I get 10 permutations; (4) redo everything again but this time use criteria 2 (k=2) (I have more criteria 1:n).

Suupose I have y <- rbeta(10000, 2, 5) and I only want to see only the density plot from x = 0 to x = 1 How do I do this? -- Thanks, Jim. [[alternative HTML version deleted]]

Hi all, Looking at the body for the function rnorm, I see that the body of the function is: .Call(C_rnorm, n, mean, sd) I want to implement functions that generate normal (and other) random variables. Now, I understand that I can perfectly well just call the R wrapper for these functions and that will be almost indistinguishable for most purposes, but for whatever reason I wanted to try and

I have a problem in where i generate m independent draws from a binomial distribution, say draw1 = rbinom( m , size.a, prob.a ) then I need to use each draw to generate a beta distribution. So, like using a beta prior, binomial likelihood, and obtain beta posterior, m many times. I have not found out a way to vectorize draws from a beta distribution, so I have an explicit for loop

HiI want to construct a logliikelood function in RHere is the situationy=number of particles emitted in 1 hr period~pois(30)p=probability of detection of radiation particlesx=number of particles detected by a radiation detector~pois(30p)where p~beta(a,1)I have to calculate the loglikehood for a for the range a(2,50)I wish to simulate 100 random samples for each aHere is my code:-m=481n=100x =

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

I am new to R and learned to program 10 years ago in C++. I am currently working a project that looks at the distribution of randomly generated beta values. I take 20 random beta values find their sum, repeat 100000 times. Here is my code that it took me 4 hours to get s=numeric(length=100000) for(i in 1:100000){ pop=(rbeta(n=20,shape1=2,shape2=1)) s[i]=sum(pop) } So now I have them all in