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- W2332315073 abstract "Linearization methods are customarily adopted in sampling surveys to obtain approximated variance formulae for estimators of statistical functionals under the design-based approach. In the present paper, following the Deville [Variance estimation for complex statistics and estimators: linearization and residual techniques. Surv Methodol. 1999;25:193–203] approach stemming from the concept of design-based influence function, we provide a general result for linearizing a large family of population functionals which includes many of the inequality measures considered in social, economic and statistical studies, such as the Gini, Amato, Zenga, Atkinson and Generalized Entropy indices. The feasibility of our theoretical results is assessed by some simulation studies involving real and artificial data." @default.
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- W2332315073 date "2016-03-16" @default.
- W2332315073 modified "2023-09-26" @default.
- W2332315073 title "Linearization of inequality indices in the design-based framework" @default.
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- W2332315073 doi "https://doi.org/10.1080/02331888.2015.1135924" @default.
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