similar to: smallest/biggest number

Dear R experts, How to find out the index of minimum or maxmum number in a vetor or data.frame? For example, a= n price 1 50 -2 100 0 200 -1 300 ...... I want to find out the row which the n is the smallest or largestest and extract the price. Thanks Ted -- View this message in context:

so it could be zero in both cases when given column has 0 set in it -- View this message in context: http://r.789695.n4.nabble.com/how-to-find-smallest-non-negative-and-biggest-non-positive-number-in-a-matrix-column-tp3077870p3077870.html Sent from the R help mailing list archive at Nabble.com.

Hello, I am trying to interface in my teaching some elementary probability with Monte Carlo ideas. In sampling from a finite population, the number of distinct samples of size 'k' from a population of size 'n' , when individuals are selected with replacement and the selection order does not matter, is choose(n + k -1, k). Does anyone have a suggestion about how to simulate

Anyone who can help me with the following question? How can I add weight to [x,y] coordinates on a graph/scatterplot? Background: Monte Carlo simulation generated 730,000 [x,y] coordinates with a weight attached (from 0-0.5). Both x and y are rounded and fit on a raster with x-axis 0-170 months (smalles unit = 1 month) and y-axis 0-6 (smallest unit=0.1). I would like every [x,y] to add its

How many distinct values can rnorm return? I assume that rnorm manipulates runif in some way, runif uses the Mersenne Twister, which has a period of 2^19937 - 1. Given that runif returns a 64 bit precision floating point number in [0,1], the actual period of the Mersenne Twister in a finite precision world must be significantly less. One of the arguments for Monte Carlo over the bootstrap is

Hi everyone, I am running a monte carlo and am getting an error that I haven't the slightest clue where to begin figuring it out. The error is as follows: Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-NA) cases In addition: Warning message: In ltm.fit(X, betas, constraint, formula, con) : Hessian matrix at convergence is not positive definite;

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

Hi, Is there a way to plot non numerical data in R? Specifically, I have an array, say with 1000 entries, where each entry is a string of 4 characters (in any order, 24 possibilities in my case). I would like on the y-axis all the strings that are in the array as labels. The x-axis I would like labeled 0 to 1000. The line is to show how the strings change as we move through the array.

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 - I am doing some monte carlo simulations comparing bayesian (using Plummer's jags) and maximum likelihood (using lmer from package lme4 by Bates et al). I would like to know if there is a way I can flag nonconvergence and exceptions. Currently the simulations just stop and the output reads things like: Error in optim(.Call("lmer_coef", x, 2, PACKAGE = "Matrix"), fn,

I am having the same problem as one Rebecca Sela(see bellow). On 21/12/2007 12:07 AM, Rebecca Sela wrote: >* I am trying to optimize a likelihood function using NLMINB. After running without a problem for quite a few iterations (enough that my intermediate output extends further than I can scroll back), it tries a vector of parameter values NaN. This has happened with multiple Monte Carlo

Hello all, I would like to know what the difference is between chisq.test and fisher.test when using the Monte Carlo method with simulate.p.value=TRUE? Thank you -- View this message in context: http://r.789695.n4.nabble.com/Difference-in-Monte-Carlo-calculation-between-chisq-test-and-fisher-test-tp2322494p2322494.html Sent from the R help mailing list archive at Nabble.com.

> Dear R experts, >I am sorry for my inability. >I have the following dataset: > Qtot Itot >1 73 684 >2 64 451 >3 71 378 >4 65 284 >5 47 179 >6 31 117 >7 19 69 > >Now I need to perform Monte Carlo Pertutation test underlaying the following condition. > > >Condition > >In order to choose randomly (5000 times) for the Qtot

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, I created several figures and their titles should appear like this: Figure 1: Monte Carlo results for alternative estimators of structural parameters (N = 100, T = 5) Because N and T change across figures, my code includes the following lines: N.set <- 100 T.set <- 5 mtext(“Figure 1: Monte Carlo results for alternative estimators of structural

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%

HI R-users, I am trying to repeat an example from Rayner and Best "A contingency table approach to nonparametric testing (Chapter 7, Ice cream example). In their book they calculate Durbin's statistic, D1, a dispersion statistics, D2, and a residual. P-values for each statistic is calculated from a chi-square distribution and also Monte Carlo p-values. I have found similar p-values

Hi Group, I have a matrix, and I would like to replace numbers less than 0 by the smallest minimum number. Below is an small matrix, and the loop I used. I would like to get suggestions on the "R way" to do this. Thanks, Juliet # example data set mymat <- structure(c(-0.503183609420937, 0.179063475173256, 0.130473004669938, -1.80825226960127, -0.794910626384209, 1.03857280868547,

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]]

.... 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: