similar to: Use of hosking.sim R function

Hi, I tried to simulate an ARIMA model by using arima.sim(), say arima.sim(n=100,list(order=c(1,0,1),ar=0.6,ma=0.9,sd=1), but the acf and pacf of simulated data using acf() and pacf() are so much different from the theoritcal acf and pacf. For instance, in my case, ar=0.6 and ma=0.9, so the acf for all lags should be greater than 0 based on the theoritical calculation, but the acf of simulated

1) L-moments: Does anyone know of any R code that will calculate these? (I'm aware that these can be calculated in S-Plus using the EnvironmentalStats for S-Plus module.) 2) Hosking & Wallis (1997): "Regional frequency analysis: an approach based on L-moments" Does anyone know of any code in either R or S-plus that implements the discordancy and homogeneity methods described

I am having problems with the package dse. I just installed R 2.2.1 and reinstalled all packages. I am running Windows XP Pro with all updates. Below there are two examples of error messages generated when trying to execute some simple programs. The code was taken directly from the package documentation. Any help on this will be greatly appreciated. Merry Christmas Fernando

Hello there fellow R users, Im trying to fit a gls model to data which has serial correlation in the errors e(t)=p*e(t-1). However I dont seem to be having much luck in erradicating the autocorrelation in the residuals. I have created the following example. library(nlme) x<-rnorm(100) y<-3+2*x y<-y+arima.sim(100,model=list(ar=(0.6)))+rnorm(100,0,0.2) #Create a data set with first

hi! some time ago i have purchased card reader for scanning sim-card. it have usb inerface. in set was cd with soft (as usual only for windows) soft on cd: usb-driver installer sim max 5.16 & i try to run it on mandriva2008 kernel 2.6.22.9 first i try to install 'usb-driver installer.exe' then install sim max 5.16(it's 2 prog.: sim editor and sim scanner),but that's wrong way!

I have been trying to simulate from a time series with trend but I don't see how to include the trend in the arima.sim() call. The following code illustrates the problem: # Begin demonstration program x <- c(0.168766559, 0.186874000, 0.156710548, 0.151809531, 0.144638812, 0.142106888, 0.140961714, 0.134054659, 0.138722419, 0.134037018, 0.122829846, 0.120188714,

In some time series simulations I'm doing, I occasionally want the model to be ``white noise'', i.e. no model at all. I thought it would be nice if I could fit this into the arima.sim() context, without making an exceptional case. I.e. one ***could*** do something to the effect if(length(model)==0) x <- rnorm(n) else x <- arima.sim(model,n) but it would be more suave if one

Dear Sir, I think I found a bug in the function arma.sim, which is defined in the help page of the function filter: arma.sim <- function(n, ar = NULL, ma = NULL, sigma = 1.0) { x <- ts(rnorm(n+100, 0, sigma^2), start = -99) if(length(ma)) x <- filter(x, ma, sides=1) if(length(ar)) x <- filter(x, ar, method="recursive") as.ts(x[-(1:100)]) } I am using R

Hello, I have used the arima.sim function to generate a lot of time series, but to day I got som results that I didn't quite understand. Generating two time series z0 and z1 as eps <- rnorm(n, sd=0.03) z0 <- arima.sim(list(ar=c(0.9)), n=n, innov=eps) and z1 <- arima.sim(list(ar=c(0.9)), n=n, sd=0.03), I would expect z0 and z1 to be qualitatively similar. However, with n=10 the

Hi! I'm considering to buy a GSM bridge to save on GSM calls. Right now they are offering subscriptions with 200 minutes each month for almost nothing, however the 400 minutes subscriptions are considerably more expensive. Most GSM bridges can cater for 2 SIM cards, is there a way for Asterisk to run the first SIM card to it's max and then switch to the second? (If one call would

I am trying to simulate time series data for an ar(1) and ma(1) process. I want the error term to have either a t distribution with 1 degree of freedom or a normal distribution with mean=0 and sd=1. Here is my code: error.model=function(n){rnorm(n,mean=0, sd=1)} data<-arima.sim(model=list(ar=c(0.1)), n=1000, n.start=200, start.innov=rnorm(200,mean=0, sd=1), rand.gen=error.model ) data

Hi, I am using the arima.sim function to generate some AR time series. However, the function does not seem to produce exactly the same time series when I specify the innov parameter. For example > r <- rnorm(300) > x <- arima.sim(300, model=list(order=c(1,0,0),ar=c(.96)), innov=r, n.start=10) > y <- arima.sim(300, model=list(order=c(1,0,0),ar=c(.96)), innov=r, n.start=10) >

Apologies for thickness - I'm sure that this operates as documented and with good reason. However... My understanding of arima.sim() is obviously imperfect. In the example below I assume that x1 and x2 are similar white noise processes with a mean of 5 and a standard deviation of 1. I thought x3 should be an AR1 process but still have a mean of 5 and a sd of 1. Why does x3 have a mean of ~7?

Full_Name: Gang Liang Version: 1.7.1 OS: Debian/Woody Submission from: (NULL) (192.6.19.190) > print(arima.sim(list(ar=.3,order=c(1,1,1)), 30)) [1] 0.00000000 0.10734243 0.02907301 -1.23441659 -0.98819317 -2.82731975 [7] -2.69052512 -4.22884756 -5.02820635 -5.41514613 -6.20486350 -7.01040649 [13] -6.78121289 -5.41111810 -4.96338053 -5.42395408 -6.22741444 -5.75228153 [19] -6.07346580

Hi Everyone, I'm having a problem with arima.sim. Namely specifying inital values for the series. If I generate a random walk > vs = rnorm(100,0,1) > xs = cumsum(vs) and fit an ARIMA(1,0,0) to it > xarima = arima(xs,order=c(1,0,0)) > xarima Call: arima(x = xs, order = c(1, 0, 0)) Coefficients: ar1 intercept 0.9895 8.6341 s.e. 0.0106 6.1869 I should

Hello, I have a question about function arima.sim I tried to somulate a AR(1) process, with no innovation, no error term. I used this code: library(forecast) e=rnorm(100,mean=0,sd=0) series=arima.sim(model=list(ar=0.75),n=100,innov=e)+20 Then I tried to applicate ti this series auto.arima function: mod1<-auto.arima(series,stepwise=FALSE,trace=TRUE,ic='aicc') The best model returned

Hi List; Is there an Digium cards support GSM SIM cards so we can fix an SIM card to be used for calls within mobiles as it is less rate? Or I have to use an FXS to SIM adaptor? If yes, then anyone advise a models and prices? Regards Bilal ____________________________________________________________________________________ Be a better friend, newshound, and know-it-all with Yahoo!

Hi, I have been using arima.sim from the stats package recently, and I'm wondering why I get different results when using what seem to be the same parameters. For example, I've given examples of three different ways to run arima.sim with what I believe are the same parameters. It's my understanding from the R documentation that rnorm is the default function for rand.gen if not

Hey, as a bloddy beginner in R I want to simulate a Arima (2,1,0) process with R. My problem is, that I don't know how to specify the AR. For a ARIMA(1,1,0) I use the following syntax: S <- arima.sim(list(order=c(1,1,0), ar=0.9), n=100). I think it is a stupid question with an easy answer. But when I google the only results are arima.sim for an ARIMA (1,1,0). Regards, Chris --

Hi all, I want to make initial VoIP authentication process from asterisk server to be based on EAP-SIM authentication of Freeradius server (so it will be not necessary to insert account datas in the asterisk database). Is there any way of doing that from Freeradius and Asterisk? Or at least, is there any way to sync the EAP-SIM data on Freeradius to asterisk server? thank you -------------- next