Weighted lead forecasting optimizes the forecasting parameters to minimize the average error measure between the historical data and the fit values, offset by 1, 2, and so on, up to the specified number of periods (lead value). It uses the simple lead technique for several lead periods, averages the error measure over the periods, and then optimizes this average value to obtain the method parameters.
Use weighted lead forecasting when the future forecast for several periods is most important. For example, suppose your company must order extremely expensive manufacturing components one and two months in advance, making forecasts for all the time periods up to two months out the most important.
In weighted lead forecasting:
Simple lead error measures are calculated for lead values from 1 to the specified lead value.
The weighted lead RMSE is calculated as the average of the simple lead RMSEs starting from lead value = 1 to the specified lead value period. For a lead value of 3, simple lead error measures for 1, 2, and 3 are obtained and then averaged to get the weighted lead RMSE.
Method parameters are then obtained by minimizing the weighted lead RMSE.
After the parameters are obtained, forecasts for future periods and the standard errors for those forecasts are calculated as for standard forecasts.
If method parameters are provided by the user, weighted lead forecasting is performed as described previously. If the parameters are not provided, they are optimized to minimize the weighted lead error measure, such as weighted lead RMSE.
After parameters are optimized, the fit and the forecast are then calculated as for the standard forecasting method. For a lead value = 1, weighted lead forecasting is the same as simple lead forecasting and standard forecasting.