similar to: Create Artificial Binary Matrix based on probability

Dear All, I am trying to fill in a blank vector ("a") with one value at a time, with the value of the number of rows in a randomized dataset with rowSums=0. Below is the code I've got so far, but what I want to be as the last line is " a[1st NA,]=nz" such that this will run until all of my NAs are replaced with an integer value based on randomizations.

Dear All, I wrote a function for cluster analysis to compute cophenetic correlations between dissimilarity matrices (using the VEGAN library) and cluster analyses of every possible clustering algorithm (SEE ATTACHED) http://old.nabble.com/file/p26288610/cor.coef.R cor.coef.R . As it is now, it is extremely long, and for the future I was hoping to find a more efficient way of doing this sort of

Dear all, I think I must be going crazy.... If I do > mean(rpois(1000000, 14)) I get: [1] 13.50420 and again: > mean(rpois(1000000, 14)) [1] 13.49896 > mean(rpois(1000000, 14)) [1] 13.50161 > mean(rpois(1000000, 15)) [1] 14.49250 > mean(rpois(1000000, 15)) [1] 14.49897 > mean(rpois(1000000, 14.5)) [1] 13.99689 > mean(rpois(1000000, 14.5)) [1] 13.9963 This was on a platform

Full_Name: Kjetil Kjernsmo Version: Version 1.0.0 OS: osf1 Submission from: (NULL) (129.240.28.227) Dear all, I have come across another really strange bug in rpois. If I do > rpois(1, 1000000 * rpois(1, 10000)) sometimes it hangs, and hangs... On my XP1000 alphaev6 workstation, it seems to happen more frequently than on other machines. I started a session on an older computer, and from

I know I should probably RTFM for this question, but could someone tell me if R supports the idea of "viewing source" on any particular function you want to use? If I want to "view source" on the rpois() function, for example, can I do somethink like: source(rpois) To see how the function is implemented? Regards, Paul Meagher Datavore Productions 50 Wood Grove Drive

Hi all, It's been a while since i've used R and I can't remember how to do the following: i have a = rpois (100000, x) b = rpois (100000, y) what is the code to show that a>b, b>a and a=b to show just the number of occurances? at the moment when I type a>b I get a nice long list of true or false. so i'm hoping to have the following a>b > 35000 b>a > 25000

Hi, Can anyone help to write a more elegant version of my code? I am sure this can be put into a loop but I am having trouble creating the objects b1,b2,b3,...,etc. b1 <- rigamma(50,1,1) theta1 <- rgamma(50,0.5,(1/b1)) sim1 <- rpois(50,theta1) b2 <- rigamma(50,1,1) theta2 <- rgamma(50,0.5,(1/b2)) sim2 <- rpois(50,theta2) b3 <- rigamma(50,1,1) theta3 <-

The R poisson random generator rpois appears to have a bug for theta 10 or larger. The sample mean of the pseudo variates is too small: sample mean approx theta - 0.5. I use Version 1.1.1 (August 15, 2000) Of R on a Dell OptiPlex computer with the Windows XP Professional operating system. Has this bug been fixed in later versions? (I found another reported rpois bug, but it appears to be

Dear List: I have the follow code: y <- replicate(10,replicate(8,sum(rnorm(rpois(1,5))))) Now I need to apply the following condition to _every_ randomly generated Normal number in the code above: x - max(0,x-15) + max(0,x-90), where x represents the individual Normal numbers. In other words, the said condition needs to be applied before replicate(...(replicate(...(sum(...))) takes place.

Dear all, I'm a bit confused about the output from functions that generates random values, e.g. rpois. I'm using 0.65.1 on Digital UNIX alphaev6. If I say > rpois(10,5) output is not unexpectedly: [1] 4 6 5 7 6 5 2 2 5 3 but I figured that if I go: > rpois(10,1:10) I would get a 10x10 matrix as output, with random values for each of the vector elements in the row vectors, but

Hello, All: ????? Consider: Browse[2]> set.seed(1) Browse[2]> rpois(9, 1e10) NAs produced[1] NA NA NA NA NA NA NA NA NA ????? Should this happen? ????? I think that for, say, lambda>1e6, rpois should return rnorm(., lambda, sqrt(lambda)). ????? For my particular Monte Carlo, I have replaced my call to rpois with a call to the following: ?rpois. <- function(n,

So imagine rpois is changed, such that the storage mode of its return value is sometimes integer and sometimes numeric. Then imagine the case where lambda is itself a realization of a random variable. Do we really want the storage mode to inherit that randomness? On 1/19/20 10:47 AM, Avraham Adler wrote: > Maybe there should be code for 64 bit R to use long long or the like? > > On

On 2020-01-19 09:34, Benjamin Tyner wrote: >> ------------------------------------------------------------------------ >> Hello, All: >> >> >> ? ????? Consider: >> >> >> Browse[2]> set.seed(1) >> Browse[2]> rpois(9, 1e10) >> NAs produced[1] NA NA NA NA NA NA NA NA NA >> >> >> ? ????? Should this happen? >>

Hello, 1. After I generate a 100x50 matrix by x3<-matrix(0,100,50);for (i in 1:100) {x1<-rpois(50, mu[i]);x2<-x1; x2[runif(50)<.01]<-0; x3[i,]<-x2}, 2. I want to calculate means and sample variances of each row and create a new matrix 100x2; 3. I then want to repeat above procedure 500 times so that eventually I will have 500 100x2 matrices. Would someone mind helping me to

????? This issue arose for me in simulations to estimate confidence, prediction, and tolerance intervals from glm(., family=poisson) fits embedded in a BMA::bic.glm fit using a simulate.bic.glm function I added to the development version of Ecfun, available at "https://github.com/sbgraves237/Ecfun".? This is part of a vignette I'm developing, available at

Hello I have 4 1000*1000 matrix A,B,C,D. I want to use the corresponding element of the 4 matrices. Using the "for loop" as follow: E<-o for (i in 1:1000) {for (j in 1:1000) { E<-fisher.test(matrix(c(A[i][j],B[i][j],C[i][j],D[i][j]),2))#call fisher.test for every element } } It is so time-consuming Need vectorization Yours sincerely ZhaoXing Department of

On 2020-01-19 13:01, Avraham Adler wrote: > Crazy thought, but being that a sum of Poissons is Poisson in the sum, > can you break your ?big? simulation into the sum of a few smaller > ones? Or is the order of magnitude difference just too great? ????? I don't perceive that as feasible.? Once I found what was generating NAs, it was easy to code a function to return pseudo-random

On 1/20/20 4:26 AM, Martin Maechler wrote: > Coming late here -- after enjoying a proper weekend ;-) -- > I have been agreeing (with Spencer, IIUC) on this for a long > time (~ 3 yrs, or more?), namely that I've come to see it as a > "design bug" that rpois() {and similar} must return return typeof() "integer". > > More strongly, I'm actually pretty

I issue the following: > d <- density(rnorm(1000)) > d and get: Call: density.default(x = rnorm(1000)) Data: rnorm(1000) (1000 obs.); Bandwidth 'bw' = 0.2235 x y Min. :-3.5157 Min. :2.416e-05 1st Qu.:-1.6892 1st Qu.:1.129e-02 Median : 0.1373 Median :7.267e-02 Mean : 0.1373 Mean :1.367e-01 3rd Qu.: 1.9639

Hi, I'm completely new to R, I am all at sea with the interface and the confusing help files, so would appreciate some help to do a simple task. Need to present the mean and variance of 100 different samples of poisson distributions (N=1000, with fixed lambda) in a file in two columnns, and then produce histograms. So far I have figured out: > N <- 1000 > x <- rpois(N, 3.1) ,