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Weighted bootstrap method for fuzzy data

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Abstract

The weighted bootstrap contained in the monograph by Barbe and Bertail in Lecture Notes in Statist, Springer (1995) is a simple and straight-forward method for calculating approximated biases, standard deviations, confidence intervals, and so forth, in almost any nonparametric estimation problem. In this paper, we consider another example, namely, fuzzy data, and use the weighted bootstrap to answer several questions concerning the minimum inaccuracy estimator (Corral and Gil in Stochastica 8:63–81, 1984): (a) What is the standard error of this estimator? (b) What is a reasonable confidence interval for such a estimate? The validity of weighted bootstrap method is investigated using a real data and computer simulation.

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  1. Department of Mathematics Education, National Hsinchu Teachers College, Hsin-Chu, Taiwan

    Wen-Liang Hung

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  1. Wen-Liang Hung
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Correspondence to Wen-Liang Hung.

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Hung, WL. Weighted bootstrap method for fuzzy data. Soft Comput 10, 140–143 (2006). https://doi.org/10.1007/s00500-004-0436-x

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