summary:
ARIMA models provide another approach to time series forecasting. Exponential smoothing and ARIMA models are the two most widely used approaches to time series forecasting, and provide complementary approaches to the problem. While exponential smoothing models are based on a description of the trend and seasonality in the data, ARIMA models aim to describe the autocorrelations in the data.
Questions
- Which is an ARIMA model?
- What the ARIMA model accounts for in the time series?
- What is the difference between ARIMA nd ETS models?
- How to select orders of ARIMA models?
- How to estimate parameters of ARIMA models?
- How to produce forecast using ARIMA models?
- How to specify and estimate ARIMA models using R functions in
fable?
Schedule
Readings
