In this chapter, we discussed time-series methods for forecasting the demand one period ahead, i.e., in period t-1, we generate a forecast y_t for the demand in period t. Suppose instead that we wish to forecast multiple periods ahead, i.e., in period t-1, we generate a forecast y_t-1,t+k for the demand in period t+k, for k 0. Explain how to adapt each of the following methods to handle this case:

a) moving average b) double exponential smoothing c) linear regression

2.7 (Multiple-Period-Ahead Forecasts) In this chapter, we discussed time-series methods for forecasting the demand one period ahead, i.e., in period t1, we generate a forecast 3t for the demand in period t. Suppose instead that we wish to forecast multiple periods ahead, i.e., in period t1, we gencrate a forecast yt1,t+k for the demand in period t+k, for k0. Explain how to adapt each of the following methods to handle this case: a) Moving average b) Double exponential smoothing c) Lincar regression