A Simple Method for Approximating the Variance of a Complicated Estimate
A Simple Method for Approximating the Variance of a Complicated Estimate
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一种近似复杂估计方差的简单方法
DOI：
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发表时间：
1971
期刊：
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通讯作者：
R. Woodruff
中科院分区：
文献类型：
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作者：
R. Woodruff
计算复杂样本估计量方差的一种常用方法是先用泰勒近似将变量的非线性形式化为线性形式。本文展示了在这个线性表达式中，仅仅通过颠倒选择单元和分量变量之间的顺序就可以得到有用的结果。该方法是完全通用的（假设样本足够大，以证明使用泰勒近似），不涉及任何限制（a）的形式的估计，（B）的数量的随机变量的估计，（c）的类型，复杂性或数量的样本设计中涉及的估计。
Abstract A method often used for computing the variance of a complicated sample estimate is to first apply the Taylor approximation to reduce non-linear forms of the variables to linear form. This article shows the useful results which can be obtained by merely reversing the order between selection units and component variables in this linear expression. The method is completely general (assuming that the samples are large enough to justify using the Taylor approximation) involving no restrictions on (a) the form of the estimate, (b) the number of random variables involved in the estimate, (c) the type, complexity or number of the sample designs involved in the estimate.