Box-Jenkins

The Box-Jenkins approach is a method for analyzing and predicting future values of a time series, like sales or temperature data. It involves identifying patterns such as trends or seasonal effects, estimating a mathematical model that captures these patterns, and then using this model to forecast future observations. This process, known as ARIMA modeling, helps understand the underlying processes driving the data and provides more accurate predictions by systematically refining the model based on historical information. It’s widely used in various fields for effective and data-driven decision making.