Mean squared error of prediction in models for studying ecological and agronomic systems
Mean squared error of prediction in models for studying ecological and agronomic systems
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DOI：
10.2307/2531995
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发表时间：
1987-09
期刊：
影响因子：
1.9
通讯作者：
D. Wallach;B. Goffinet
中科院分区：
文献类型：
--
作者：
D. Wallach;B. Goffinet
预测的均方误差（MSEP）被认为是一个标准，用于研究生态和农艺系统的模型进行评估。结果表明，在文献中讨论了这种模型的不同来源的错误，可以严格定义的MSEP。这种模型经常出现的情况是，模型参数的确定与用于测试模型的数据无关，并且感兴趣的群体被构造成亚群体。它表明，在这种情况下，获得估计的MSEP和个人的误差贡献可以减少到经典的问题，估计方差分量的单向随机模型。为了进行比较，这里也讨论了从用于测试模型的相同数据估计参数的情况。
The mean squared error of prediction (MSEP) as a criterion for evaluating models used for studying ecological and agronomic systems is considered. It is shown that the different sources of error that have been discussed in the literature for such models can be rigorously defined in terms of the MSEP. A situation that occurs frequently for such models is that the model parameters are determined independently of data used to test the model, and the population of interest is structured in subpopulations. It is shown that in this case obtaining estimators of MSEP and of the individual error contributions can be reduced to the classic problem of estimating components of variance in a oneway random model. For comparison, the case where the parameters are estimated from the same data used to test the model is also addressed here.