An empirical Bayes procedure for adaptive forecasting of shrimp yield

In order to make decisions regarding when to harvest cultured shrimp, short -term forecasts of future growth must be compared with expected future cost s and changes in the value of the shrimp harvested. As with most agricultur al products, researchers and business professionals collect and maintain da ta on the various factors that influence growth. Though many general fixed relationships between, say salinity, temperature, time and turbidity are kn own, exactly how these affect a particular crop changes from year to year. Vitality of the stock, unmeasured characteristics of the pond, and other fa ctors which vary over time have a significant affect on the yield of a harv est. Consequently, to make reasonable short-term forecasts, forecasting mod els must include both the general factors gathered from past experience and crop specific variations from these overall effects. This paper presents a method of obtaining such a forecasting equation using a general mixed mode l setup currently available in many computer packages. These general formul as are illustrated with a real life example. SAS code necessary to implemen t the analysis is also included, The paper concludes by presenting a genera l equation for short-term forecasts using the estimates obtained from a SAS analysis. (C) 2000 Elsevier Science B.V. All rights reserved.