Using Bayesian Estimation and Decision Theory to Determine the Optimal Level of Nitrogen in Cotton
Brorsen, B. Wade
2013

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Abstract

Improved software now makes Bayesian estimation a strong alternative to nonlinear maximum likelihood. Bayesian methods were used to estimate a linear response stochastic plateau for cotton and were shown to provide estimates similar to maximum likelihood. Optimal levels of nitrogen were lower than recommended levels.

Details

Title
Using Bayesian Estimation and Decision Theory to Determine the Optimal Level of Nitrogen in Cotton
Keywords
Author(s)
Brorsen, B. Wade
Subject(s)
Issue Date
2013-01
Publication Type
Conference Paper/ Presentation
DOI and Other Identifiers
10.22004/ag.econ.142951
Record Identifier
https://ageconsearch.umn.edu/record/142951
PURL Identifier
http://purl.umn.edu/142951
Language
English
Total Pages
14
JEL Codes
C11
Q12
Record Appears in
Southern Agricultural Economics Association (SAEA) > 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida

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