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Outlier detection and treatment in industrial sampling survey
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 Title & Authors
Outlier detection and treatment in industrial sampling survey
Joo, Young Sun; Cho, Gyo-Young;
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Outliers in surveys can have a large effect on estimates of totals. This is especially true in business surveys where the populations are drawn are typically skewed. In this paper, we discussed the practical development and implementation of methods to identify and deal with outliers. A detection method is based on quartile method and detected outlier is processed in various ways. The study examines two versions of winsorised estimators with three different cut-off thresholds for each one. For the simulation study, four types of weight transformation function have been considered.
Outlier detection;outlier treatment;winsorization;weight reduction;
 Cited by
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