A Spatio-temporal Model for Agricultural Yield Prediction

dc.creatorTokovenko, Oleksiy
dc.creatorDorfman, Jeffrey H.
dc.creatorGunter, Lewell F.
dc.date2017-04-01T20:13:49Z
dc.date.accessioned2026-07-09T05:11:49Z
dc.descriptionThe paper presents a spatio-temporal statistical model of agricultural yield prediction based on spatial mixtures of distributions. The proposed method combines several hierarchical and sequential Bayesian estimation procedures that allow the general problem to be addressed with a series of simpler tasks, providing the required flexibility of the model while decreasing the complexity associated with the large dimensionality of the spatial data sets. The data used for the study are 1970 - 2009 annual Iowa state county level corn yield data. The spatial correlation hypothesis is studied by comparing the alternative models using the posterior predictive criterion under squared loss function.
dc.identifierdoi:10.22004/ag.econ.61673
dc.identifierhttps://ageconsearch.umn.edu/record/61673/files/otokovenkoAAEA2010.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/61673
dc.identifier.urihttp://hdl.handle.net/123456789/560330
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/61673
dc.titleA Spatio-temporal Model for Agricultural Yield Prediction
dc.typeText

Archivos