Choice of an appropriate bending factor using prior knowledge of the parameters
Choice of an appropriate bending factor using prior knowledge of the parameters
复制标题
使用参数的先验知识选择适当的弯曲系数
DOI：
10.1111/j.1439-0388.1991.tb00162.x
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发表时间：
1991
影响因子：
2.6
通讯作者：
A. Essl
中科院分区：
文献类型：
--
作者：
A. Essl
通过蒙特卡罗模拟开发并评估了一种在遗传选择指数构建中选择适当弯曲因子的新方法。该方法的主要特点是使用的弯曲因子最大化了真实和估计的聚合基因型之间的相关性，通过计算公式中的猜测值（先验）替换（未知）群体参数。该程序以及与指数选择相关的其他一些程序的效率在 336 个不同的参数和样本情况下进行了研究，每个参数有 1000 个重复。研究发现，即使在所使用先验的假设可靠性较差的情况下，与所研究的所有其他程序相比，所提出的方法的效率也很高。例如，使用相当于来自样本量为 400 的半同胞分析的估计值的先验，建议的方法平均仅比理论上的最佳可能弯曲程序效率低 3.3%。另一方面，与未调整的指数相比，当样本量为 400、800 和 1600 时，观察到的改善分别为 20.1%、8.7% 和 2.2%。该方法的另一个重要优点是它能够自适应改变参数和样本条件。此属性允许其普遍应用于任何形式的索引选择。总体而言，弯曲对指标选择的改进是显着的，并且遗传选择指标的构建条件越不利，改进越大。
A new method for the choice of an appropriate bending factor in the construction of genetic selection indices was developed and evaluated by Monte Carlo simulation. The main feature of the proposed method is that the bending factor used maximises the correlation between true and estimated aggregate genotype, replacing the (unknown) population parameters through guessed values (priors) in the computation formula. The efficiency of this and some other procedures relevant to index selection was investigated on 336 different parameter and sample situations with 1000 replicates each. It was found that even in the case where the assumed reliability of the used priors was poor, the efficiency of the proposed method compared with all other procedures investigated was high. For example, using priors equivalent to estimates originating from a half-sib analysis with a sample size of 400, the suggested method was on average only 3.3% less effective than the best possible bending procedure from theory. On the other hand, compared with an unadjusted index, the observed improvement was 20.1, 8.7 and 2.2% when the sample sizes were 400, 800 and 1600 resp. A further essential advantage of the proposed method is its self-adaptation to changing parameter and sample conditions. This property allows its universal application to any form of index selection. In general, the improvement of index selection by bending was substantial, the improvement being larger the more unfavourable the conditions for the construction of genetic selection indices are.