similar to: [Fwd: Re: tseries Package for R]

Wizon wrote: > I am using Mac OSX. I am first starting to use R and have not > installed any packages yet. I searched through the CRAN site for a > Mac OSX version, but did not find one. I downloaded the tar.gz > package. Will this work on the Mac? Is there a way to get a package > that I don't have to compile? Thanks in advance for your help. > > Adam > >

Hello, I am having a problem with the get.hist.quote command (tseries library) in the Windows version. This problem is not happening is the Linux version (Mandrake 8.2). Attached is the error message, for an example included in the help file. Also the R.Version() details is attached. Please, do you know if there is a workaround ? Thanks, Carlos. ++++++++++++++++++++++++ ERROR MESSAGE

Hi ALL: I am trying to use get.help.quote from library(tseries). I tried to run the example from help(get.hist.quote) but R complained. Here is the command I used and the response: ibm <- get.hist.quote(instrument = "ibm", start = "1998-01-01") trying URL

Hi, I'm running R 2.4.1 on Fedora Core 6 and am unable to install the tseries package. I've resolved a few problems getting to this point, by running a yum update, installing the gcc-gfortran dependency, but now I'm stuck. Could someone please point me in the right direction? ========R install.packages output ======= ==================================

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

Hi I am looking to perform a discrete mean-variance optimisation, specifically to maximise the ratio of portfolio mean over portfolio standard deviation for a portfolio of several hundred stocks through discrete position size holdings in each stock, where all position sizes must be elements of a small finite set of integer amounts which include zero. I don't think any of the standard R

Hi I am looking to perform a discrete mean-variance optimisation, specifically to maximise the ratio of portfolio mean over portfolio standard deviation for a portfolio of several hundred stocks through discrete position size holdings in each stock, where all position sizes must be elements of a small finite set of integer amounts which include zero. I don't think any of the standard R

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

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

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

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

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]]

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

Has anyone successfully check/build tseries for MacOSX? It seems like there is the same problem with symbols duplications. The -m like option does not seem to help. stefano

Norbert Klink wrote: > Hi! > > I would like to use your tseries GARCH functionality in conjuction with > S-Plus 6 under Windows. Unfortunately, in order to make DLLs usable for > S-Plus it requires you to generate a so-called "S-Plus Chapter DLL", which > carries some S-Plus specific overhead. Loading your DLLs as they are > wouldn't work. Trying to compile the

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)) :

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 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.