Forecasting-on-Retail-Data-using-R

• Forecasted for two years on the Retail Data in Australian Capital Territory with R and understand effect of COVID-19 on it. • Forecasting was performed by implementing classical decomposition, exponential smoothing and ARIMA models. • Seasonal Naïve was best model as it captured seasonality of data and subsequently a forecast for 2 years was generated with 95% confidence interval, highlighting future trend.