Question

Identify eight major forms of time-series models (mathematical methods) used for forecasting?

1) ARIMA
2) Exponential Smoothing
3) Holt-Winters
4) Autoregressive Integrated Moving Average
5) Seasonal Autoregressive Integrated Moving Average
6) Vector Autoregression
7) GARCH
8) State Space Models

Answer 1

There are eight major forms of time-series models used for forecasting: ARIMA, Exponential Smoothing, Holt-Winters, Autoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA), Vector Autoregression (VAR), GARCH, and State Space Models.

Step-by-step explanation:

The eight major forms of time-series models used for forecasting are:

1. ARIMA
2. Exponential Smoothing
3. Holt-Winters
4. Autoregressive Integrated Moving Average (ARIMA)
5. Seasonal Autoregressive Integrated Moving Average (SARIMA)
6. Vector Autoregression (VAR)
7. GARCH
8. State Space Models

These models are used to analyze and forecast time-based data, such as stock prices, sales data, or weather patterns. Each model has its own mathematical framework and assumptions, and they are chosen based on the characteristics and patterns observed in the data being analyzed.