REPRESENTATIONS OF MULTI-ATTRIBUTE GRAIN QUALITY

dc.creatorDeVuyst, Eric A.
dc.creatorJohnson, D. Demcey
dc.creatorNganje, William E.
dc.date2017-04-01T14:07:48Z
dc.date.accessioned2026-07-09T04:12:05Z
dc.descriptionGrain quality is typically measured via several attributes. As these attributes vary across shipments and time, grain quality can be described using multivariate probability or frequency distributions. These distributions are important in modeling blending opportunities inherent in various grain shipments. For computational reasons, it is usually necessary to represent these distributions with a small set of discrete points and probabilities. In this analysis, we suggest a representation method based on Gaussian quadrature. This approach maintains the blending opportunities available by preserving moments of the distribution. The Gaussian quadrature method is compared to a more commonly used representation in a barley blending model.
dc.identifierdoi:10.22004/ag.econ.31149
dc.identifierhttps://ageconsearch.umn.edu/record/31149/files/26010275.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/31149
dc.identifier.urihttp://hdl.handle.net/123456789/546318
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/31149
dc.titleREPRESENTATIONS OF MULTI-ATTRIBUTE GRAIN QUALITY
dc.typeText

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