Hansi Weissensteiner wrote:
>Hello!
>
>I installed the fSeries package to get some farima time-series which i tried
>with farimaSim, but unfortunately i got always an error. I tried it this
way:
>
>
>
>>farimaSim(n = 1000, model = list(ar = 0.5, d = 0.3, ma = 0.1),
method="freq")
>>
>>
>
>Error in farimaSim(n = 1000, model = list(ar = 0.5, d = 0.3, ma = 0.1), :
> ... used in an incorrect context
>
>
In the function definition of farimaSim the dots argument is missing.
Replace or overwrite farimaSim by the following function.
I have to aplogize for any inconveniances caused by this bug.
The bug will be fixed in the next version of Rmetrics.
Diethelm Wuertz
farimaSim function(n = 1000, model = list(ar = c(0.5, -0.5), d = 0.3, ma = 0.1),
method = c("freq", "time"), ...)
############ ^^^^^^^^^^ #### Insert the dots!!!!
{ # A function implemented by Diethelm Wuertz
# Description:
# Simulates a FARMA Time Series Process
# Note:
# Splus-Like argument list
# Example:
# armaSim(model = list(ar = c(0.5, -0.5), d = 0.2, ma = 0.1))
# armaSim(model = list(d = 0.2, ma = 0))
# armaSim(model = list(d = 0.2))
# FUNCTION:
# Settings:
innov = NULL
n.start = 100
start.innov = NULL
rand.gen = rnorm
# Simulate:
if (!is.list(model))
stop("model must be list")
if (is.null(innov))
innov = rand.gen(n, ...)
n = length(innov)
if (is.null(start.innov))
start.innov = rand.gen(n, ...)
n.start = length(start.innov)
# AR PART:
p = length(model$ar)
if (p == 1 && model$ar == 0)
p = 0
if (p) {
minroots = min(Mod(polyroot(c(1, -model$ar))))
if (minroots <= 1) stop("ar part of model is not
stationary")
}
# MA PART:
q = length(model$ma)
if (q == 1 && model$ma == 0)
q = 0
if (n.start < p + q)
stop("burn-in must be as long as ar + ma")
# DIFFERENCING:
## if (model$d < 0) stop("d must be positive ")
dd = length(model$d)
if (dd) {
# FRACDIFF if "dd" is a non-integer value:
d = model$d
if (d != round(d) ) {
TSMODEL = "FRACDIFF"
} else {
TSMODEL = "ARIMA" }
} else {
d = 0
TSMODEL = "ARIMA"
}
# ARMA:
if (TSMODEL == "ARIMA") {
stop("d is a short range model")
}
if (TSMODEL == "FRACDIFF") {
if (p == 0) model$ar = 0
if (q == 0) model$ma = 0
mu = 0
# Use Fortran Routine from R's contributed fracdiff package:
# This is a BUILTIN function ...
x = .Fortran("fdsim", as.integer(n), as.integer(p),
as.integer(q),
as.double(model$ar), as.double(model$ma), as.double(model$d),
as.double(mu), as.double(rnorm(n + q)), x = double(n + q),
as.double(.Machine$double.xmin),
as.double(.Machine$double.xmax),
as.double(.Machine$double.neg.eps),
as.double(.Machine$double.eps),
PACKAGE = "fSeries")$x[1:n]
}
# Return Value:
ans = as.ts(x)
attr(ans, "model") = model
ans
}
The result will be:
farimaSim(n = 1000, model = list(ar = 0.5, d = 0.3, ma = 0.1),
method="freq")
Time Series:
Start = 1
End = 1000
Frequency = 1
[1] 3.2301357515 2.7050870252 3.4878581467 4.1825601460 5.1286599175
[6] 5.5220029973 5.1488261085 5.9423142081 3.5078481961 2.1189096844
[11] 2.5885700846 2.2224732255 3.0389690791 2.8123050401 2.6096020908
[16] 2.3095398924 1.4900953088 2.6017795027 3.5148157279 3.4317135045
...
[991] -0.5745174996 0.9022402358 -0.5675451281 1.4723458150 2.2187064082
[996] 1.6818662030 0.3170217298 0.9290833661 0.5800528928 -1.6796471062
attr(,"model")
attr(,"model")$ar
[1] 0.5
attr(,"model")$d
[1] 0.3
attr(,"model")$ma
[1] 0.1
>Some ideas?
>
>Regards,
>
> ___
> _ /_|_| Hansi Weissensteiner
>/o\__/O\= csae1552 at uibk.ac.at
>
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