Modeling Crop Yield Distributions from Small Samples

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dc.creatorUpadhyay, Bharat Mani
dc.creatorSmith, Elwin G.
dc.date2017-04-01T14:11:54Z
dc.date.accessioned2026-07-09T04:22:49Z
dc.descriptionAccurately modeling crop yield distributions is important for estimation of crop insurance premiums and farm risk-management decisions. A major challenge in the modeling has been due to small sample size. This study evaluated potentials of L-moments, a recent concept in mathematical statistics, in modeling crop yield distribution. Five candidate distributions were ranked for describing the wheat yields. The selected distribution was robust for small sample and was invariant to de-trending. The result was consistent with that from the maximum likelihood and goodness-of-fit method.
dc.identifierdoi:10.22004/ag.econ.34161
dc.identifierhttps://ageconsearch.umn.edu/record/34161/files/sp05up01.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/34161
dc.identifier.urihttp://hdl.handle.net/123456789/549031
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/34161
dc.titleModeling Crop Yield Distributions from Small Samples
dc.typeText

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