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Evaluating Decision Rules for Nitrogen Fertilization
Author(s) -
Antoniadou T.,
Wallach D.
Publication year - 2000
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2000.00420.x
Subject(s) - estimator , nonparametric statistics , decision rule , nitrogen fertilizer , mathematics , bias of an estimator , computer science , optimal decision , minimum variance unbiased estimator , profit (economics) , mathematical optimization , econometrics , statistics , fertilizer , artificial intelligence , economics , decision tree , chemistry , organic chemistry , microeconomics
Summary. It is important, both for farmer profit and for the environment, to correctly dose nitrogen fertilizer for crop growth. Fertilizer recommendations are embodied in decision rules, which give a recommended dose of nitrogen (N) as a function of information available at the time the decision is made. In this paper, we first propose a criterion for evaluating decision rules. The proposed criterion is the expectation of the objective function when the decision rule is implemented. The major problem here is the estimation of this criterion. Two estimators are considered, a model‐based and a nonparametric estimator. A simulation study shows that, in essentially all cases, the nonparametric estimator is better or no worse than the model‐based estimator. The bias in the nonparametric estimator is always very small.