similar to: Combinatorial Optimisation

Hi all I am trying to solve a combinatorial optimization problem. Basically, I can reduce my problem into the next problem: 1.- Given a NxN grid of points, with some values in each cell 2.- Find the combination of K points on the grid such that, the maximum mean value is obtained I took the Travel SalesMan problem example in ?optim documentation. I am not sure if I have understood correctly

I am writing code in C and would like to call R's functions samin and vmmin (optimization routines: simulated annealing and BFGS) I do not understand how to create and pass in the function (as well as the extra arguments it needs) I am optimizing. I have read the R Extensions manual but it is still unclear to me. Could you give me some pointers and/or direct me to some example code which

Hello, I wonder why the control parameter REPORT is not supported by method SANN. Looking into optim.c I found an internal constant: #define STEPS 100 ... and decreasing this to 10 helped me fine-tuning the annealing parameters in an actual problem. Is there any reason why not passing nREPORT to samin and setting something like: STEPS = nREPORT / tmax Thomas P. -- Thomas Petzoldt

Follow the example in tseries, we can simulated a GARCH(0,2), n <- 1100 a <- c(0.1, 0.5, 0.2) # ARCH(2) coefficients e <- rnorm(n) x <- double(n) x[1:2] <- rnorm(2, sd = sqrt(a[1]/(1.0-a[2]-a[3]))) for(i in 3:n) # Generate ARCH(2) process { x[i] <- e[i]*sqrt(a[1]+a[2]*x[i-1]^2+a[3]*x[i-2]^2) } x <- ts(x[101:1100]) and x is a GARCH(0,2). But, I would like to know how

Dear list, I was trying to use the R API for optimization method "Simulated annealing" void samin(int n, double *x, double *Fmin, optimfn fn, int maxit, int tmax, double temp, int trace, void *ex); but I encountered the following problem: The implementation of the function samin (as seen in src/main/optim.c) passes its void * argument "ex" into the function

I'm preparing some code to compute the optimal geometry of stressed solids. The core of the calculations is the optimization of elastic energy using the simulated annealing method implemented in the R optim() rutine. I've defined a function to compute this "energy" scalar (the fn parameter for optim) and prepared a list with the arrays defining the geometry and the elastic

Ok I made Jarque-Bera test to the residuals (merv.reg$residual) library(tseries) jarque.bera.test(merv.reg$residual) X-squared = 1772.369, df = 2, p-value = < 2.2e-16 And I reject the null hypotesis (H0: merv.reg$residual are normally distributed) So I know that: 1 - merv.reg$residual aren't independently distributed (Box-Ljung test) 2 - merv.reg$residual aren't indentically

Anyone know if there's an R package somewhere that supports estimation of a linear regression model with GARCH error process? There's a garch command in the tseries package, but unless I'm missing something it is restricted to the univariate case, i.e. you can fit a GARCH model to a single time-series but not estimate a model with GARCH errors. -- Allin Cottrell Department of

Hi,I try to calcualte AIC or Loglik to GARCH model,But the Packege Tseries do not deal with them.How can I calculate AIC or Loglike to GARCH Model By Packege Tseries? Thanks. ____________________________________________________ Free Internet Access NOW! In Alexandria, Ismaileya, Suez, Portsaid, Hurgadha, Sharm Banha, Shebin El-Kom, Damietta, Tanta, Zagazig, Mansoura, Damanhour, Assyout, Qena

Dear all, Can garch function fit also t-innovations or only Gaussian innovations? -- With kind regards -- Lepo pozdravljeni -- Gr??e (Gr?ezi) -- Gorazd Brumen ------------------------------- Mail 1: gbrumen at student.ethz.ch Mail 2: gorazd.brumen at fmf.uni-lj.si Tel.: +41 (0)1 63 34906 Homepage: valjhun.fmf.uni-lj.si/~brumen

Hi there, Does anyone know if R has a function for testing whether a time series is stationary?? Thanks in advance, Wayne Dr Wayne R. Jones Statistician / Research Analyst KSS Group plc St James's Buildings 79 Oxford Street Manchester M1 6SS Tel: +44(0)161 609 4084 Mob: +44(0)7810 523 713 KSS Ltd A division of Knowledge Support Systems Group plc Seventh Floor St James's

Preallocation Instruction Scheduling with Register Pressure Minimization Using a Combinatorial Optimization Approach G. Shobaki, M. Shawabkeh and N. Abu-Rmaileh ACM Transactions on Architecture and Code Optimization (TACO). vol. 10, issue 3, Article 14 (Sept. 2013) http://dx.doi.org/10.1145/2512432 Regards Ghassan Shobaki, PH.D Assistant Professor Department of Computer Science Princess Sumaya

R-guRus , ARMA function in tseries, seems to be calculating the AR coeff 's as coef <- lm(xx[,1]~xx[,lag$ar+1])$coef [*snipped* from around line 77,] I'd like to modify this model with another term somewhat in these lines lm(xx[,1] ~xx[,lag$ar+1]+mvgsignal)$coef where mvgsignal is a moving average signal based on some indicators, the question is could i simply hack into

Dear R People: I have a weekly time series. How do I put this into the ts command, please? That is, what do I use for frequency, please? R version 1.5.1 for Windows. Thanks in advance. Sincerely, Erin mailto: hodgess at uhddx01.dt.uh.edu -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html

I would like to know if there is a way to test no correlaction in time series ? cov(r_t, r_t-1)=0 And r_t are homoscedastik and independent. Thanks [[alternative HTML version deleted]]

Hello all, I would like how to modelized a time serie with AR-ARCH process. It can be used arma and garch functions in tseries package for build ar process or a garch process, but how can it be modelized a ar-garch model ? Thanks [[alternative HTML version deleted]]

Hello! I have the following combinatorial problem. Consider the cumulative sums of all permutations of a given weight vector 'w'. I need to know how often weight in a certain position brings the cumulative sums equal or above the given threshold 'q'. In other words, how often each weight is decisive in raising the cumulative sum above 'q'? Here is what I do: w <-

Hi R specialists, The na.omit.ts() method fails when the time series contains internal NA's. How can these automatically be removed? > spectrum(ts.mNDII, na.action=na.omit) Error in na.omit.ts(as.ts(x)) : time series contains internal NAs How can the na.action be activated correctly? > acf(ts.Lin, type=c("correlation"), na.action=na.omit) Error in na.omit.ts(as.ts(x)) :

Dear all, Is there a test in R for the randomness of a sequence of observations (e.g. to test the random number generator)? Specifically I am looking for autocorrelations which are not necessarily linear in nature, which the acf function does not seem to be flexible enough to detect as it tests for linear autocorrelation. Thanks in advance, Paul.

I wondered was people on this list felt about this article: http://www.voxeu.org/index.php?q=node/2363 which talks about the problems of obtaining sound answers in numerical optimisation in settings such as MLE or NLS. -- Ajay Shah http://www.mayin.org/ajayshah ajayshah at mayin.org http://ajayshahblog.blogspot.com <*(:-? -