similar to: Simulations / repetitions help!

Some background: I have some data on structural dependencies in a base of code artifacts. The dependency structure is reflected in terms of relative node degrees, with each node representing some code unit (just as an example). This gives me real data of the following form (sorry for the longish posting): dat1 <- c(0.00245098039215686, 0, 0, 0, 0, 0, 0, 0, 0.0563725490196078, 0, 0, 0,

Dear All, we have released version 0.6 of the igraph package today. This is a major new version, with a lot of new features, and (sadly) it is not completely compatible with code that was written for the previous igraph versions. (See "Major new features" below for details.) I have included below a list of (bigger) changes. Please see the details in the release notes and the NEWS

Dear All, we have released version 0.6 of the igraph package today. This is a major new version, with a lot of new features, and (sadly) it is not completely compatible with code that was written for the previous igraph versions. (See "Major new features" below for details.) I have included below a list of (bigger) changes. Please see the details in the release notes and the NEWS

On 5/8/2018 12:26 PM, varin sacha via R-help wrote: > > Dear R-experts, > > Here below the reproducible example. I am trying to get the average of the 100 results coming from the "lst" function. I have tried lst$mean and mean(lst). It does not work. > Any help would be highly appreciated > > #################### > > ?## R script for getting MedAe and

Hi, I've had this problem for a while and tackled it is a quite dirty way so I'm wondering is a better solution exists: If we have two vectors: v1 = c(0,1,2,3,4) v2 = c(5,3,2,1,0) How to remove one instance of the "3,1" / "1,3" double? At the moment I'm using the following solution, which is quite horrible: v1 = c(0,1,2,3,4) v2 = c(5,3,2,1,0) ft <-

Hi, I have a data frame consisting of coordinates on a 10*10 grid, i.e. > example x y 1 4 5 2 6 7 3 6 6 4 7 5 5 5 7 6 6 7 7 4 5 8 6 7 9 7 6 10 5 6 What I would like to do is return an 10*10 matrix consisting of counts at each position, so in the above example I would have a matrix where, for example, cell [4,5] contains 2 and [6,7] contains 3. At the

Dear R-experts, Here below the reproducible example. I am trying to get the average of the 100 results coming from the "lst" function. I have tried lst$mean and mean(lst). It does not work. Any help would be highly appreciated. #################### ?## R script for getting MedAe and MedAeSQ from HBR model on Testing data install.packages("robustbase") install.packages(

Hi all, I'm having some troubles with the Quantreg package. I am using R version 2.10.0, and have downloaded the most recent version of Quantreg (4.44) and SparseM (0.83 - required package). However, when I try to run an analysis (e.g. fit1<-rq(y~x, tau=0.5)) I get an error message saying that the function "rq" could not be found. I get the same message when I try to search

Hello all. I'm doing a large scale simulation study and every so often I get an error that stops the simulation. I would like to ignore the errors and identify the particular iterations where they occurred. I have tried: options(error = expression(NULL)) which I thought would ignore the error, but the simulation is still stopped when an error occurs. I do not think try() is a good idea

Hi all, I am a biostatistician and I have developed my own ranking system for clinical data. I would like to test the efficiency of it w.r.t. to other ranking systems. I would like to simulate the data and after assigning ranks to my observed scores(after neglecting dropouts), observe the type I error. If I want to do a Kruuskal Wallis type of test, what test statistic should I use to test for a

Hello I would like to generate covariance matrix with autoregressive structure. I saw some functions in nlme such as corAR1 for example but I don't know how to use it for my goal. Could someone help me or advise me another function? Thank you in advance Caroline

Greetings, I'm trying to find a function to generate a random landscape consisting of x by y cells, allows a specification of number of classes and their proportional abundance in the landscape. Does R support such a function ? Thanks in advance Steve Steve Friedman, Assistant Professor Center for Global Change and Earth Observations Michigan State University East Lansing, Michigan

Hi everyone, I recently ran a simulation on a computer using R that was hooked up to a UPS. There was one time when the power was out for length and the computer shut down. I was worried that I had lost the simulation, but upon booting the machine up, I heard the processor kick in. It sounded like the simulation had resumed. Does anyone have any experience with this? Because I live in

Dear R-users, I am trying to perform some simulations from a model defined by ordinary differential equations. I would be grateful if someone could indicate some functions/packages/examples I could look at. Thank you in advance. Sebastien

Hello, I have estimated an ARIMA model and I would like to make simulations from this estimated model 1,5 and 10 steps ahead. Does anybody know how to do this? Thank You Felipe Parra [[alternative HTML version deleted]]

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,

Hello! I am writing you because I could not plot the confidence envelopes for functions Jest, Jcross, Jdot, Jmulti, and L, using the Spatstat package. I have already understood how to do that for Kest or Jest, that is: JEnv <- plot(envelope(PPPData, Jest)) Where PPPData is my ppp object. However, for Jcross I must specify the two marks I want to analyse. That is, usually I would get the

1) The Pareto P(alfa) distribution is defined by its density f(x|alfa) =alfa*X^(-alfa-1) over (1 to infinity). Show that it can be generated as the -1/alfa power of a uniforme variate. Plot the histogram and the density. 2) The Poisson distribution P(lambda) is connected to the exponential distribution through the Poisson process in that it can be simulated by generating exponential random

Hello R-help list I'm trying to run 1 billion iterations of a code with calls to random distributions to implement a data generating process and subsequent computation of various estimators that are recorded for further comparison of performance. I have two question about how to achieve this: 1. the most important: on my laptop, R gives me an error message saying that it cannot

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