On Wed, 20 Jun 2012, Sanzad Siddique wrote:
I have tried the ARIMA command in GRETL with the attached time series
data.
The time series is constructed with the below formula ( a- is normal random
values):
z(t) = 0.50 + 0.50*z(t-1) + 0.40*z(t-2) + a(t)-0.25*a(t-1)
-0.75*a(t-2);
with the arima command (arima 2 0 2; 1), for order (2,2) , I am getting the
below output:
coefficient std. error z p-value
---------------------------------------------------------
const 4.96454 0.0275435 180.2 0.0000 ***
phi_1 -0.447238 0.789760 -0.5663 0.5712
phi_2 -0.0272188 0.390533 -0.06970 0.9444
theta_1 0.751567 0.787981 0.9538 0.3402
theta_2 -0.00643631 0.629626 -0.01022 0.9918
I'm seeing those results using your data, but I'm not seeing
anything similar if I construct data on this basis in gretl.
<hansl>
nulldata 2000
setobs 7 2006/06/02
series a = normal()
series z = 5 # the unconditional mean
z = 0.5 + 0.5*z(-1) + 0.40*z(-2) + a - 0.25*a(-1) - 0.75*a(-2)
arima 2 0 2 ; z
arima 2 0 2 ; z --conditional
</hansl>
Typical result:
const 5.00054
phi_1 0.533660
phi_2 0.357096
theta_1 -0.288852
theta_2 -0.711148
The constant is not close to 0.5, but that depends on how mean
terms are handled. See section 23.2 of the Gretl User's Guide.
In this case z* = 0.5 + 0.5z* + 0.4z*, so z* = 5. If you want
to see the constant given as approx 0.5, use conditional ML.
Allin Cottrell