*
* Example of moving average smoothing, pp 143-145
*
data(unit=input) 1 11 shipments
 200 135 195 197.5 310 175 155 130 220 277.5 235
*
* The filter instruction with TYPE=LAGGING computes the average of the input data
* for periods t,t-1,...,t-span+1
*
filter(type=lagging,span=3) shipments / ma3
filter(type=lagging,span=5) shipments / ma5
*
* The forecast values for t is just the smoothed value for t-1. This instruction
* handles that.
*
set ma3fore = ma3{1}
set ma5fore = ma5{1}
*
* This analyzes the forecasts errors
*
@uforeerrors(title="MA(3) forecasts") shipments ma3fore
@uforeerrors(title="MA(5) forecasts") shipments ma5fore
*
graph(footer="Figure 4-4 Shipments of Electric Can Openers with Moving Average Forecasts",$
 key=attached,klabels=||"Observed values","MA(3)","MA(5)"||) 3
# shipments
# ma3fore
# ma5fore