similar to: Systematic resampling (in sequential Monte Carlo)

===== Summary ===== Version 0.1.0 provides the initial release of RcppSMC, an integration of the SMCTC template classes for Sequential Monte Carlo and Particle Filters (Johansen, 2009, J Statistical Software, 30:6) with the Rcpp package for R/C++ Integration (Eddelbuettel and Francois, 2011, J Statistical Software, 40:8). RcppSMC allows for easier and more direct access from R to the

===== Summary ===== Version 0.1.0 provides the initial release of RcppSMC, an integration of the SMCTC template classes for Sequential Monte Carlo and Particle Filters (Johansen, 2009, J Statistical Software, 30:6) with the Rcpp package for R/C++ Integration (Eddelbuettel and Francois, 2011, J Statistical Software, 40:8). RcppSMC allows for easier and more direct access from R to the

Hi, This is an announcement for a package that has been up on CRAN since March 2006 but was never announced. The package is Mchtest - for Monte Carlo hypothesis tests allowing sequential stopping. The idea is to use the sequential probability ratio test boundaries to stop resampling for a Monte Carlo hypothesis test such as a bootstrap or permutation test. This means that you will take many

Hi, This is an announcement for a package that has been up on CRAN since March 2006 but was never announced. The package is Mchtest - for Monte Carlo hypothesis tests allowing sequential stopping. The idea is to use the sequential probability ratio test boundaries to stop resampling for a Monte Carlo hypothesis test such as a bootstrap or permutation test. This means that you will take many

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

I use fGarch package to estimate AR(1)-ARCH(1) process for a vector of returns. Then, using the estimated parameters I want to simulate 10 000 sample paths where each path has the same length as the vector of returns. So the first line of the code is: spec=garchSpec(model=list(ar= 0.440270860, omega=0.000374365,alpha=0.475446583 , mu=0, beta=0))---- The only way I can think of generating 10 000

Dear R user: I wonder if it is possible to run monte carlo simulation with dse2 package(MonteCarloSimulations function) using ordinary differential equation. How do I define the model? Or if there are any functions which can run monte carlo simulation using ordinary differential equation. Please give me some comments. Thanks in advance!!

Hi, Dear R users, I'm wondering if I can do Monte Carlo Simulation in R. My problem is like this: I know variable X follows Gamma distribution with shape parameter 0.067 and scale parameter 0.008. The sum of the X is 2000. I need R help me to simulate a vector of X that satisfies both the probability distribution and the sum. Anyone has a clue to this? Much appreciated. Regards Garry

I'm testing some different formulations of pairwise interaction point processes in Spatstat (version 1.11-6) using R 2.5.0 on a Windows platform and I wish to simulate them using the Metropolis-Hastings algorithm implemented with Spatstat. Spatstat utilizes Fortran77 code with the preprocessor RatFor to do the Metropolis-Hastings MCMC, but the Makefile is more complicated than any I have

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

Dear all, I have a question about the chisq.test command. As an option one can chose the computation of p-values by Monte-Carlo simulation (simulate.p.value=T). Is there any documentation available how this calculations are done and how this simulation based test behaves in small samples? Thanks Klaus Abberger University of Konstanz, Germany [[alternate HTML version deleted]]

What about "Rtips" at http://lark.cc.ukans.edu/~pauljohn/R/statsRus.html ? Regards, Heinrich. > -----Urspr?ngliche Nachricht----- > Von: rossini at blindglobe.net [mailto:rossini at blindglobe.net] > Gesendet: Mittwoch, 26. Juni 2002 14:48 > An: r.hankin at auckland.ac.nz > Cc: r-help at stat.math.ethz.ch > Betreff: Re: [R] sapply() and Monte Carlo > > >

Dear Sir, Please tell me how to perform monte-carlo white noise test using R. Thanking you with regards S.Sijikumar -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To:

Hello Dear, I am trying to generate samples by using Monte Carlo simulation. For example, 1000 samples, Exponential distribution (f(x), lambda=0.0005, 0<=x<=360) Is there any package for Monte Carlo or just use random sample generation function? Many thank you for your help in advance, Jin -- View this message in context:

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.

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]]

Dear All, I have to programme a Monte Carlo EM for an Generalized Linear Mixed Model, Binomial Response and Normal Random Effect, Could anyone give me a hand sending some R code? TIA Francisco ___________________________________________________________ 1GB gratis, Antivirus y Antispam Correo Yahoo!, el mejor correo web del mundo http://correo.yahoo.com.ar

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 trying to simulate binary outcome data for a logistic regression Monte Carlo study. I need to eventually be able to manipulate the structure of the error term to give groups of observations a random effect. Right now I am just doing a very basic set up to make sure I can recover the parameters properly. I am running into trouble with the code below. It works if you take out the object

Hello, I am doing simulations, and I generate a list at each iteration (with three component matrices in the example below), saving the results in a list. For example, after two iterations, I have something like > str(sim.theta) List of 2 $ :List of 3 ..$ : num [1:6, 1:4] -3.67 -1.07 -2.99 -18.38 -3.26 ... ..$ : num [1:6, 1:6] -7.56 -3.14 -4.99 1.03 2.79 ... ..$ : num [1:6, 1:4]