###
### create an artificial quarterly dataset with 256 observations
###

nulldata 256
setobs 4 1960:1
set seed 24072023

###
### generate an arma(2,2) process
###

y = filter(normal(), {1,0.5, -0.3}, {1.4, -0.8})

###
### compute information criteria for all models up to 4,4
###

# optionally, one can append the "--quiet" option
arima 4 4 ; y --lagselect 


###
### pick up the best model
###

# choose one of "AIC, "BIC", "HQC"
crit = "HQC" 

# select the appropriate column of the $test matrix
colsel = 2 + instrings(strsplit("AIC BIC HQC"), crit)

# select the appropriate row of the $test matrix
best = iminc($test[,colsel])

# set p and q
p = $test[best, 1]
q = $test[best, 2]

# estimate the "best" model
arima p q ; y