Predictive Densities for Shire Level Wheat Yield in Western Australia
Rainfall during the germination, growing and flowering periods is a major determinant of wheat yield. The degree of uncertainty attached to a wheat-yield prediction depends on whether the prediction is made before or after the rainfall in each period has been realised. Bayesian predictive densities that reflect the different levels of uncertainty in wheat-yield predictions made at four different points in time are derived for five shires in Western Australia.
|Date of creation:||Jan 2001|
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- Coelli, Tim J., 1992. "Forecasting Wheat Production Using Shire Level Data," 1992 Conference (36th), February 10-13, 1992, Canberra, Australia 146430, Australian Agricultural and Resource Economics Society.
- Chatfield, Chris, 1993. "Calculating Interval Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 143-44, April.
- Chatfield, Chris, 1993. "Calculating Interval Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 121-35, April.
- Geweke, John, 1986. "Exact Inference in the Inequality Constrained Normal Linear Regression Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(2), pages 127-41, April.
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