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Iterative method for reducing the impact of outlying data points: Ensuring data quality

机译:减少外围数据点影响的迭代方法:确保数据质量

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摘要

Data editing is essential to check the survey data for possible data problems. Outlying data values are frequently encountered in sample surveys. Consequently, in working with data, the correctness of the reported values must be verified, and if a reported value constitutes an outlier, its appropriate treatment needs to be considered. In this paper, the Iterative method for the reducing the impact of outlying data points is proposed. The novelty of the Iterative method for the reducing the impact of outliers is the following: an iterative approach for determining the outlying data points is proposed; outliers are determined considering the impact of conjoined factors; estimation of weight coefficients of the outliers and estimation of the total measurement error of the non-linear regression model is carried out.
机译:数据编辑对于检查调查数据中可能存在的数据问题至关重要。样本调查中经常会遇到外围数据值。因此,在处理数据时,必须验证报告值的正确性,如果报告值构成异常值,则需要考虑对其进行适当的处​​理。本文提出了一种减少外围数据点影响的迭代方法。减少离群值影响的迭代方法的新颖性在于:提出了一种确定离群数据点的迭代方法;结合相关因素的影响来确定异常值;估计离群值的权重系数并估计非线性回归模型的总测量误差。

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