用卷积加权法估计尼日利亚住户调查中缺失数据

Faweya Olanrewaju, Amahia Godwin Nwanzu, Adeniran Adefemi Tajudeen
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引用次数: 0

摘要

在缺少数据的情况下,调查数据的分析变得困难。利用最小二乘和Stein规则方法,得到了感兴趣参数的估计量。在本研究中,提出的卷积加权最小二乘法和Stein规则方法与一些现有的数据完全随机缺失(MCAR)技术进行了比较。结果表明,其他方法在估计大多数参数时偶尔有用,但在MCAR假设下,无论缺失数据的百分比如何,所提出的(LSSR)方法都表现得更好。
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Estimation of Missing Data Using Convoluted Weighted Method in Nigeria Household Survey
The analysis of survey data becomes difficult in the presence of missing data. By the use of Least Squares and Stein Rule method, estimator for the parameters of interest can be obtained. In this study, proposed convoluted Weighted Least Squares and Stein Rule method is compared with some existing techniques where the data is considered missing completely at random (MCAR). The results show that other techniques are occasionally useful in estimating most of the parameter, but proposed (LSSR) technique perform better regardless of the percentage of the missing data under MCAR assumption.
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