Please, when applying the ARIMA model (p, d, q) in a series, the partial autocorrelation function shows a peak in lag 1 and another in 25 and no other statistically significant. Is there any command in R to handle these two lags only, not including 25 regressive coefficients?
ARIMA model with lag in 1 and 25 in R
3
asked by anonymous 05.11.2015 / 16:29
1 answer
3
Yes it does.
Considering the series lh of the R:
> lh
Time Series:
Start = 1
End = 48
Frequency = 1
[1] 2.4 2.4 2.4 2.2 2.1 1.5 2.3 2.3 2.5 2.0 1.9 1.7 2.2 1.8 3.2 3.2 2.7 2.2 2.2 1.9 1.9
[22] 1.8 2.7 3.0 2.3 2.0 2.0 2.9 2.9 2.7 2.7 2.3 2.6 2.4 1.8 1.7 1.5 1.4 2.1 3.3 3.5 3.5
[43] 3.1 2.6 2.1 3.4 3.0 2.9
Set the model like this:
> arima(lh, order = c(1,1,1), fixed = c(NA, 0))
Call:
arima(x = lh, order = c(1, 1, 1), fixed = c(NA, 0))
Coefficients:
ar1 ma1
-0.0404 0
s.e. 0.1443 0
sigma^2 estimated as 0.2525: log likelihood = -34.35, aic = 72.7
In this case, I'm saying that the parameter AR1 is free (estimated by the model) and MA1 is equal to zero by means of the argument fixed .
In your case, if you wanted to set a arima(25,1,0) with only RA coefficients 1 and 25, you could do this:
> arima(lh, order = c(25,1,0), fixed = c(NA, rep(0,23), NA))
Call:
arima(x = lh, order = c(25, 1, 0), fixed = c(NA, rep(0, 23), NA))
Coefficients:
ar1 ar2 ar3 ar4 ar5 ar6 ar7 ar8 ar9 ar10 ar11 ar12 ar13 ar14
-0.0539 0 0 0 0 0 0 0 0 0 0 0 0 0
s.e. 0.1343 0 0 0 0 0 0 0 0 0 0 0 0 0
ar15 ar16 ar17 ar18 ar19 ar20 ar21 ar22 ar23 ar24 ar25
0 0 0 0 0 0 0 0 0 0 0.2994
s.e. 0 0 0 0 0 0 0 0 0 0 0.1918
sigma^2 estimated as 0.2297: log likelihood = -33.3, aic = 72.6
The argument fixed is always a vector with the number of elements equal to the number of parameters that your model has. You can pre-specify any value for the parameters, but we usually use only 0 (when we do not want that term) and NA (when we want the parameters to be estimated by the model).
05.11.2015 / 20:14