Dear Pedro,
you might be interested in the demo "StationaryRegressorDistr" of
package "distr".
library(distr)
demo("StationaryRegressorDistr")
hth,
Matthias
[EMAIL PROTECTED] wrote:
> Thanks Prof. Ripley.
>
> My apologies for not including the code.
>
> Below I illustrate my point using the GLD package.
>
> Thank you very much for your time.
>
> Kind Regards,
>
> Pedro N. Rodriguez
>
>
> # Code begins
>
> # Simulate an ar(1) process
> # x = 0.05 + 0.64*x(t-1) + e
>
> # Create the vector x
> x <- vector(length=1000)
>
> #simulate the own risk
> e <- rnorm(1000)
>
> #Set the coefficient
> beta <- 1.50
>
> # set an initial value
> x[1] <- 5
>
> #Fill the vector x
> for(i in 2:length(x))
> {
> x[i] <- 0.05 + beta*x[i-1] + e[i]
> }
>
> #Check the AR(1)
> simulated_data_ar <- arima(x,order=c(1,0,0))
> simulated_data_ar
>
> #Using the G Lambda Distribution to fit the distribution.
> library(gld)
> resul1 <- starship(x,optim.method="Nelder-Mead")
> lambdas1 <- resul1$lambda
>
> #Plot the Distribution
> plotgld(lambdas1[1],lambdas1[2],lambdas1[3],lambdas1[4])
>
> #Random Deviates from GLD
> x_sim <-
> rgl(1000,lambdas1[1],lambdas1[2],lambdas1[3],lambdas1[4])
>
> #Fit an AR(1)
> gld_simulated <- arima(x_sim,order=c(1,0,0))
> gld_simulated
>
> #Code ends
>
>
> -----Original Message-----
> From: Prof Brian Ripley [mailto:[EMAIL PROTECTED]
> Sent: Wednesday, November 28, 2007 11:37 AM
> To: Rodriguez, Pedro
> Cc: [EMAIL PROTECTED]
> Subject: Re: [R] Simulate an AR(1) process via distributions? (without
> specifying a model specification)
>
> On Wed, 28 Nov 2007, [EMAIL PROTECTED] wrote:
>
>
>> Is it possible to simulate an AR(1) process via a distribution?
>>
>
> Any distribution *of errors*, yes. Of the process values, not in
> general.
>
>
>> I have simulated an AR(1) process the usual way (that is, using a
>>
> model
>
>> specification and using the random deviates in the error), and used
>>
> the
>
>> generated time series to estimate 3- and 4-parameter distributions
>>
> (for
>
>> instance, GLD). However, the random deviates generated from these
>> distributions do not follow the specified AR process.
>>
>
> How do you know that? Please give us the reproducible example we asked
> for (in the posting guide, at the bottom of every message), and we
> should
> be able to explain it to you.
>
>
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