Whether or not you’re getting ready for a job interview or simply brushing up in your time collection forecasting expertise, you’re in the precise place!
On this weblog, we’ll stroll by way of 10 important multiple-choice questions (MCQs) overlaying the core ideas of time collection forecasting fashions, together with ARIMA, SARIMA, and extra.
Alongside the best way, we’ll break down the solutions and clarify the mathematical reasoning behind them. Let’s dive in! 🚀
A) d
B) q
C) p
D) P
Appropriate Reply: C) p
Clarification:
In an ARIMA mannequin, the parameter p defines the autoregressive (AR) a part of the mannequin. It refers back to the variety of lagged observations that the mannequin makes use of to foretell future values. As an example, if p=2, the mannequin will depend on the earlier two values of the collection to make predictions. Mathematically, the AR a part of an ARIMA mannequin is written as: