Classic Time Series Model

Class classicTimeseries ():

Parameters

• Model – (AR, MA, ARMA, ARIMA)
• Exog - Features
• Endog – Historical value of the output
• Order – iterable -The (p,d,q) order of the model for the number of AR parameters, differences, and MA parameters to use. d is always an integer, while p and q may either be integers or lists of integers.
• Dates (optional) – array_like - An array-like object of datetime objects.
• Frequency (optional)- str - The frequency of the time-series. A Pandas offset or ‘B’, ‘D’, ‘W’, ‘M’, ‘A’, or ‘Q’. This is optional if dates are given.

Attributes

Methods

• Initialize()
• Fit()
• Predict()
• Score()

Questions

a. Are we thinking of implementing Classictimeseries models as Neural Network or as traditional models in pytorch.