similar to: Hybrid Monte Carlo algorithm (MCMC)

Dear list users, I need to learn about MCMC methods, and since there are several packages in R that deal with this subject, I want to use them. I want to buy a book (or more than one, if necessary) that satisfies the following requirements: - it teaches well MCMC methods; - it is easy to implement numerically the ideas of the book, and notation and concepts are similar to the corresponding R

Hello, I'm trying to use rsync to periodically restore a test computer from a master disk image on a separate partition. The first time I copy the data from the master partition to the target partition, everything works as expected. But if I do the operation again, rsync indicates that it is copying lots of files that have not changed. More significantly, the disk usage on the target volume

Hi all, Running simulations, I'm generating market response to 2 factors X&Y.. There is no closed form for the market response.. The results are store in a matrix Z(X <- seq(.02,.98,.02), Y <- seq(.01,.19,.01)).. For optmization purpose I need to approximate the values for any factor X in 0,02-0,98 and Y in 0,01-0,19 How can I do it ? For one factor : Xn-1 < x <= Xn

Hi all I've a continuous variable and I want to test (graphically, plotting observed and theoretical distr, qqplot) whether it follows some formal distribution. (some thing close to Ricci document : Fitting distributions with R, Feb05). The distribution I want to fit is a truncated Gamma at 1 (the minimal value is 1), P(x)=Pgamma(rate,x)/(1-Pgamma(rate,x<1)) NB : changing the variable

Hi all, I've just installed R on my Mac & PC. The base demo run fine.. But I'm encountering several pb with some packages (installed using CRAN binaries using the menu) - Lattice: > demo(lattice,package='lattice') demo(lattice) ---- ~~~~~~~ Type <Return> to start : > require(grid) [1] TRUE > old.prompt <- grid.prompt(TRUE) > old.settings

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:

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 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