similar to: Monte Carlo chisq test

chisq.test with simulate.p.value=TRUE uses the Patefield algorithm, this is not documented, and the original reference is not given, as it ought to be. The reference is: Patefield,W. M. (1981) An efficient method of generating r * c tables with given row and column totals (algorithm AS 159). Applied Statistics 30, 91-97. Kjetil Halvorsen

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.

(I resend because my previous text is break. sorry..) I have a question about equalize_2.4.18.patch. I use a kernel 2.4.25. And I have multi-processor(Xeon dual) machine. I had patch equalize_2.4.18.patch file. And I had check ‘symmetric multi-processing support’ kernel compile option. When I use that kernel, the system is down. But, I had not check ‘symmetric multi-processing support’

Dear useRs I am looking for a way to randomise the values within a matrix: the conditions are that the sums of the rows and the sums of the columns should remain the same as in the original matrix. Any help would be appreciated Cheers Yann

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

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:

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

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, 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,

===== 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