Optimal designs when the variance is a function of the mean.
Optimal designs when the variance is a function of the mean.
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当方差是均值的函数时的最佳设计。
DOI：
10.1111/j.0006-341x.1999.00925.x
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发表时间：
1999
期刊：
影响因子：
--
通讯作者：
Wong,WK
中科院分区：
文献类型：
--
作者：
Dette,H;Wong,WK
当响应的方差是其均值的函数时，我们开发了非线性模型的局部最优设计。以双参数Michaelis-Menten模型为例，我们证明了最优设计取决于异方差的类型和变异的大小。此外，我们的结果表明，在广泛的异方差模式下，同方差优化设计具有很高的效率，并且对参数的标称值相当不敏感。
We develop locallyD-optimal designs for nonlinear models when the variance of the response is a function of its mean. Using the two-parameter Michaelis–Menten model as an example, we show that the optimal design depends on both the type of heteroscedasticity and the magnitude of the variation. In addition, our results suggest that the homoscedasticD-optimal design has high efficiency under a broad class of heteroscedastic patterns and that it is fairly insensitive to nominal values of the parameters.