Time Series Models

By now we have a strong foundational understanding of various concepts essential for time series analysis. The rest of the course will focus on the following:

1. A theoretical understanding of the important time series models (White Noise, AutoRegressive (AR), Moving Average (MA), ARMA.
2. The ARIMA model and how various time series processes can be explained by ARIMA.
3. Simulating and estimating these time series models in R.
4. Box-Jenkins (B-J) methodology for time series forecasting.
5. A comprehensive case study for time series analysis in R (With code and plots).