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Optimizing selection for function-valued traits

机译:优化功能值特征的选择

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摘要

We consider a function-valued trait z(t) whose pre-selection distribution is Gaussian, and a fitness function W that models optimizing selection, subject to certain natural assumptions. We show that the post-selection distribution of z(t) is also Gaussian, compute the selection differential, and derive an equation that expresses the selection gradient in terms of the parameters of W and of the pre-selection distribution. We make no assumptions on the nature of the ‘time–parameter t.
机译:我们考虑一个函数值特征z(t),其预选择分布为高斯分布,而适应性函数W则根据某些自然假设对优化选择进行建模。我们表明z(t)的选择后分布也是高斯分布,计算选择差分,并导出一个方程,该方程根据W的参数和预选择分布来表示选择梯度。我们不对“时间参数t”的性质做任何假设。

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