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Hi all, I'm looking for an analytic method to obtain the PDF & CDF of the sampling distribution of a given correlation (rho) at a given sample size (N). I've attached code describing a monte carlo method of achieving this, and while it is relatively fast, an analytic solution would obviously be optimal. get.cors <- function(i, x, y, N){ end=i*N

I need to calculate the probability that a sample quantile will exceed a threshold given the size of the iid sample and the parameters describing the distribution of each observation (normal, in my case). I can compute the probability with brute force simulation: simulate a size N sample, apply R's quantile() function on it, compare it to the threshold, replicate this MANY times, and count the

.... Un código más optimizado para la aproximación Monte Carlo de la distribución de IH N=10000 # tamaño simulación Monte Carlo n=5 # numero de uniformes cdf.IH <-function(x,n,N) { z=replicate(N,sum(runif(n))) apply(outer(x,z,">="),1,mean) } x=seq(0,5,.1) y=cdf.IH(x,n=n,N=N) plot(x,y,type="l") Un saludo. Olivier ----- Mensaje original ----- De:

Hi, We have recently published a paper on floating point accuracy analysis through Monte Carlo Arithmetic. We also released the open-source tool Verificarlo (https://github.com/verificarlo/verificarlo) that relies on LLVM for instrumenting floating point operations. Could you please add our paper to http://llvm.org/pubs/ ? Verificarlo: checking floating point accuracy through Monte Carlo

Dear R helpers Suppose I have a portfolio of securities with exposure to Equity, Bonds and Forex (say $ 1000000 each). Is there any fucntion in R that will help me calculate Value at Risk (VaR) using Monte carlo Simulation , Historic simulation and Variance - Covariance Simulation. With regards Maithili

Dear list: I'm hoping to tap in to the statistical expertise in the group, especially those familiar with simulation techniques. I'm finalizing a study where I obtain standard errors from two sources. The first source is a monte carlo simulation and the other source is an analytical model I have developed that appears to recover the standard errors from the simulation. All analysis are

Hi there, I am running Monte Carlo Simulations in R using ordinary "while (condition)" loops. Since the number of iterations is something like 100.000 and within each iteration a given subsample is extended sequentially it takes hours to run the simulation. Does anyone know if there is either a way to avoid using loops in Monte Carlo Simulations or how to include possible faster

Hi, R-helpers, I'm trying to use R to do a Monte Carlo simulation and need the help. What I have is a matrix that consists of the probabilities for the persons to choose zones. For example, in the matrix shown below, each column represents a person, and each row represents a zone. So, the probability that the first person will choose the 2nd zone is 30%. 25% 30% 10% 30% 20% 0% 20% 50% 60%

I've been attempting to understand the one-sample run test for randomness. I've found run.test{tseries} and run.test{lawstat}. Both use a large sample approximation for distribution of the total number of runs in a sample of n1 observations of one type and n2 observations of another type. I've been unable to find R code to generate the exact distribution and would like to see how

Hello, How can I make a monte carlo simulation on R? Regards Adel -- PhD candidate in Computer Science Address 3 avenue lamine, cité ezzahra, Sousse 4000 Tunisia tel: +216 97 246 706 (+33640302046 jusqu'au 15/6) fax: +216 71 391 166 [[alternative HTML version deleted]]

Hi, please use the following the matrix z as the example: x<-c(2,4,5,7,6,9,8,2,0) y<-matrix(x,3,3) z<-apply(y,2,function(x)x/sum(x)) z On Tue, Mar 23, 2010 at 6:59 PM, David Winsemius <dwinsemius@comcast.net>wrote: > > On Mar 23, 2010, at 9:05 PM, Hongwei Dong wrote: > > Hi, R-helpers, >> >> I'm trying to use R to do a Monte Carlo simulation and

estimados estoy considerando programar la funcion de distribucion de Irwin hall. lamentablemente no he tenido exito, pido que alguien me pueda colaborar con aquello, les quedo agradecido de antemano. -- atte. Lic. Genaro Llusco Silvestre gellusco en gmail.com Telf: 74028671 blog personal es: http://www.cientificest.blogspot.com [[alternative HTML version deleted]]

Hi, all, I'm running a monte carlo simulation with missing data. The data are arranged such that there are k columns and n rows over a set number of simulations (set to 10 right now so it runs fast while I set everything up). The data are integers, numbers 1-7 only (normal distribution). The simulations are set up and run without a hitch, including imposing NA missing values at a specified

Dear Listers; Does anybody has experience in doing simulation via Qusi-Monte carlo in R or S-plus, if so, could you like to send a small copy of your program to me, I appreciate and thanks in advance!! Frankly speaking, I am struggling to write this kind of program, while I could not figure out, painful!!!!! Best regards, Tony --------------------------------- [[alternative HTML

Hello all. I was wondering if anyone had insight into how I might generate a large number of data sets/vectors, where each of the data sets/vectors have a different name? For example, suppose I wanted to generate N data sets/vectors, each with a different name such as: Random.Data.1 <- rnorm(10, 0, 1) Random.Data.2 <- rnorm(10, 0, 1) Random.Data.3 <- rnorm(10, 0, 1) . . . . .

Hi Folks, I'm trying to learn R. One of my intentions is to do some Monte-Carlo type modelling of road "accidents". Below, to simplify things, I've appended a little program which does a 'monte-carlo' type simulation. However, it is written in a way which seems a bit un-natural in R. Could someone help me make this a bit more R-ish please? Or is there a

Hello, I am currently doing my project and I need some help. I am trying to schedule tutors for a study room where students come in and out for helps. My goal is to schedule the tutors to maximally accomodate to the flow of students that need help with math so that each tutor is given an appropriate(also consecutive) hours of schedule. I am using monte carlo simulation for this, however I have

Hello, I have a question concerning the R-function chisq.test. For example, I have some count data which can be categorized as follows class1: 15 observations class2: 0 observations class3: 3 observations class4: 4 observations I would like to test the hypothesis whether the population probabilities are all equal (=> Test for discrete uniform distribution) If you have a small sample size

Hi All, I am using canonical correspondence analysis to compare a community composition matrix to a matrix of sample spatial relationships and environmental variables. In order to parse out how much variance is explained purely by space (S/E) or the environment (E/S) I am using a conditional (partial) CCA. I want to test significance via Monte Carlo but I can not find a way to do this with a

Hi all, I am trying to implement a Monte-Carlo simulation for each cell in a spatial matrix (using mcd2 package) . I have figured out how to conduct the simulation using data from a single location (where I manually input distribution parameters into the R code), but am having trouble (a) adjusting the code to pull input variables from my various data sets and then (b) applying the entire