Predictive Densities for Shire Level Wheat Yield in Western Australia
AbstractRainfall 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.
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Bibliographic InfoPaper provided by Australian Agricultural and Resource Economics Society in its series 2001 Conference (45th), January 23-25, 2001, Adelaide with number 125645.
Date of creation: Jan 2001
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Bayesian prediction; Prediction with uncertain regressors.; Crop Production/Industries;
Other versions of this item:
- William E Griffiths & Lisa S Newton & Christopher J O’Donnell, 2008. "Predictive Densities for Shire Level Wheat Yield in Western Australia," Department of Economics - Working Papers Series 1051, The University of Melbourne.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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- Chatfield, Chris, 1993. "Calculating Interval Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 143-44, April.
- William Griffiths, 2002. "A Gibbs’ Sampler for the Parameters of a Truncated Multivariate Normal Distribution," Department of Economics - Working Papers Series 856, The University of Melbourne.
- Griffiths, W.E., 2001. "Bayesian Inference in the Seemingly Unrelated Regressions Models," Department of Economics - Working Papers Series 793, The University of Melbourne.
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