sarimax.py

"""automatic forecasting for SARIMAX models."""
import numpy as np
import pandas as pd
import statsmodels.api as sm

# Dataset
wpi1 = requests.get('http://www.stata-press.com/data/r12/wpi1.dta').content
data = pd.read_stata(BytesIO(wpi1))
data.index = data.t


def auto_order(endog, criteria='aic', d=0, max_order=(3, 3), spec=None):
    """Auto order function for SARIMAX models."""
    aic_matrix = np.zeros(p, q)
    for p in range(max_order[0]):
        for q in range(max_order[1]):
            if p == 0 and q == 0:
                continue
            # fit  the model
            mod = sm.tsa.statespace.SARIMAX(data['wpi'], order=(p, d, q))
            res = mod.fit(disp=False)
            aic_matrix[p, q] = res.aic
    min_aic = aic_matrix.min()
    p, q = np.where(aic_matrix == min_aic)

I have used the dataset for testing purpose now.

Great start, thanks for putting this up here! Can you make this a commit on your PR? It's actually easier to do the formal code review that way (I can put in line comments, etc.).

I'll go ahead and make some additional comments in the PR messages right now, just to keep things all in one place.