non Invertible of a ARIMA model

Question

I am trying to write a code to generate a series of arima model and compare different models.The code is as follow.

p=0
q=0
d=0
pdq=[]
aic=[]

for p in range(6):
    for d in range(2):
        for q in range(4):
            arima_mod=sm.tsa.ARIMA(df,(p,d,q)).fit(transparams=True)

            x=arima_mod.aic


            x1= p,d,q
            print (x1,x)

            aic.append(x)
            pdq.append(x1)



keys = pdq
values = aic
d = dict(zip(keys, values))
print (d)

minaic=min(d, key=d.get)

for i in range(3):
 p=minaic[0]
    d=minaic[1]
    q=minaic[2]
print (p,d,q)

Where 'df' is the time series data.And the output is as follow,

(0, 0, 0) 1712.55522759
(0, 0, 1) 1693.436483044094
(0, 0, 2) 1695.2226857997066
(0, 0, 3) 1690.9437925956158
(0, 1, 0) 1712.74161799
(0, 1, 1) 1693.0408994539348
(0, 1, 2) 1677.2235087182808
(0, 1, 3) 1679.209810237856
(1, 0, 0) 1700.0762847127553
(1, 0, 1) 1695.353190569905
(1, 0, 2) 1694.7907607467605
(1, 0, 3) 1692.235442716487
(1, 1, 0) 1714.5088374907164

ValueError: The computed initial MA coefficients are not invertible
You should induce invertibility, choose a different model order, or you can
pass your own start_params.

i.e for order (1,1,1) the model is non invertible. so the process stops there.How can i skip such non invertible combination of p,d,q and go on with other combination

Answer 1

Use try: ... except: ... to catch the exception and continue

for p in range(6):
    for d in range(2):
        for q in range(4):
            try:
                arima_mod=sm.tsa.ARIMA(df,(p,d,q)).fit(transparams=True)

                x=arima_mod.aic

                x1= p,d,q
                print (x1,x)

                aic.append(x)
                pdq.append(x1)
            except:
                pass
                # ignore the error and go on