similar to: Trouble with a loop

Dear friends. Please see the program below and answer if it does simulate a population of 1.000.000 families, each with at max 20000 children (typical in Denmark, you know), constructed such that each family stops having children when more boys than girls are present ? Equal numbers of boys and girls are got in the population, according to the simulation, is that obvious ? ND <- NP <-

I'm pasting below a working R file featuring a function I'd like to polish up. I'm teaching regression this semester and every time I come to something that is very difficult to explain in class, I try to simplify it by writing an R function (eventually into my package "rockchalk"). Students have a difficult time with predict and newdata objects, so right now I'm

R versions 2.1.0 to present. Examples shown were computed under Windows R-devel, current SVN, but ix86 Linux shows similar behaviour (sometimes NaN or -Inf rather than Inf, depending on the compiler and optimization level used). The replacement pgamma algorithm used from R 2.1.0 has an inadequate design and no supporting documentation whatsoever. There is no reference given to support the

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

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

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

This may not actually be an R/Splus problem, but it started off that way ..... ===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+===+=== Executive summary: ================== Simulations involving extreme value distributions seem to ``work'' when the underlying distribution is exponential(1) or exponential(2) == chi-squared_2, but NOT when the underlying distribution is

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,

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

I am working on predicitng the scores for a days worth of matches of team sports. I have already collected data for the teams for the season we are concentrating on. I have been fitting poisson models for football games and have worked out what model is best and which predictor variables are most important. We would now like to predict the probability distribution for the scores for each team.

Hi all, I have a matrix simulating migration in a spatial model. I want to be able to define movement (the values of m1, m2 and m3) as only != 0 between adjacent patches and contingent on certain conditions as defined in the function. Here is the code: WET<-function(t) {everglades$precipitation[t]} #simply reads precipitation data from a csv, value is numeric AB<-function(WET,t)

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

Would anyone be able to provide insight for the following question, please? Setting: estimation of prediction intervals for age-period-cohort models using GAMs (rate ~ s(age,period)) Method: bootstrap (Davison and Hinkley, 1997) Issue: standardisation of the residuals for resampling requires an adjustment using the diagonals of the hat matrix. Is there a simple way to get the hat values out of a

Hi, I've been playing with the standalone math library (R.1.1.1, Redhat 7 i386), and have detected a problem with rpois. Basically, the rejection step in rpois can result in an infinite loop. The simplest thing I can come up with that reproduces the problem is the following. #include <stdio.h> #include <math.h> #include <time.h> #define MATHLIB_STANDALONE #include

Dear all, I am trying to use the Matrix package to do some calculations on rather large and sparse matrices. An example of such a matrix is given below. mig<-0.2 side<-10 np<-side^2 mig.mat<-matrix(0,np,np) diag(mig.mat[1:(np-side),(side+1):np])<-mig/4 diag(mig.mat[(side+1):np,1:(np-side)])<-mig/4 diag(mig.mat[-np,-1])<-mig/4

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

Dear all, I have divided two vectors: Np.occup97.98<- as.data.frame(cbind(site = levels(sums$site), Np.occup97.98 = sums$Ant.Nptrad97.98/Ant.trad$Ant.trad97.98)) > Np.occup97.98 site Np.occup97.98 1 erken97 0.342592592592593 2 erken98 0.333333333333333 3 rormyran 0.48471615720524 4 valkror 0.286026200873362 However, at a later stage of the analysis I want >

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? >>

????? 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