任意阶无偏矩估计的计算机代数与算法。

IF 0.1 Q4 MATHEMATICS Cogent mathematics & statistics Pub Date : 2019-01-01 Epub Date: 2019-12-21 DOI:10.1080/25742558.2019.1701917
Inna Gerlovina, Alan E Hubbard
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引用次数: 4

摘要

虽然低阶的无偏中心矩估计量(如样本方差)很容易获得并经常在实践中使用,但由于冗长的数学和棘手的组合,高阶的无偏估计量的推导可能更具挑战性。此外,更高的阶数需要计算幂和乘积的估计量,这些估计量也等于这些阶数。我们开发了一种软件算法,允许用户获得任意阶的无偏估计量,并提供高达6阶的结果,包括低阶的幂和乘积。该方法还扩展到寻找几个不同种群的较高中心矩的汇总估计(例如,用于双样本测试)。我们介绍了一个R包Umoments,它计算单样本和双样本估计,并生成用于获得这些估计的中间结果。
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Computer Algebra and Algorithms for Unbiased Moment Estimation of Arbitrary Order.

While unbiased central moment estimators of lower orders (such as a sample variance) are easily obtainable and often used in practice, derivation of unbiased estimators of higher orders might be more challenging due to long math and tricky combinatorics. Moreover, higher orders necessitate calculation of estimators of powers and products that also amount to these orders. We develop a software algorithm that allows the user to obtain unbiased estimators of an arbitrary order and provide results up to the 6th order, including powers and products of lower orders. The method also extends to finding pooled estimates of higher central moments of several different populations (e.g. for two-sample tests). We introduce an R package Umoments that calculates one- and two-sample estimates and generates intermediate results used to obtain these estimators.

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