best_param.py

def best_param(model, data, pdq, pdqs):
    """
    Loops through each possible combo for pdq and pdqs
    Runs the model for each combo
    Retrieves the model with lowest AIC score
    """
    ans = []
    for comb in tqdm(pdq):
        for combs in tqdm(pdqs):
            try:
                mod = model(data,
                            order=comb,
                            seasonal_order=combs,
                            enforce_stationarity=False,
                            enforce_invertibility=False,
                            freq='D')

                output = mod.fit()
                ans.append([comb, combs, output.aic])
            except:
                continue

    ans_df = pd.DataFrame(ans, columns=['pdq', 'pdqs', 'aic'])
    return ans_df.loc[ans_df.aic.idxmin()]