Time Series Analysis and ARIMA Modeling in R

This lecture delves into time series analysis, starting with data preparation, transforming datasets into monthly time series. Stationarity is verified through ADF and KPSS tests with differencing techniques. Differenced series are analyzed using plotting, STL decomposition, and seasonal-trend interpretations. ARIMA models are fitted for forecasting, with evaluation against actual values. Seasonal and regular differencing are explored to refine data adjustments, alongside distribution...