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An R tool for computing and evaluating Fuzzy poverty indices: The package FuzzyPovertyR

Author

Listed:
  • F. Crescenzi
  • L. Mori
  • G. Betti
  • F. Gagliardi
  • A. D'Agostino
  • L. Neri

Abstract

Fuzzy set theory has become increasingly popular for deriving uni- and multi-dimensional poverty estimates. In recent years, various authors have proposed different approaches to defining membership functions, resulting in the development of various fuzzy poverty indices. This paper introduces a new R package called FuzzyPovertyR, designed for estimating fuzzy poverty indices. The package is demonstrated by using it to estimate three fuzzy poverty indices – one multi- and two uni-dimensional – at the regional level (NUTS 2) in Italy. The package allows users to select from a range of membership functions and includes tools for estimating the variance of these indices by the ad-hoc Jack-Knife repeated replication procedure or by naive and calibrated non-parametric bootstrap methods.

Suggested Citation

  • F. Crescenzi & L. Mori & G. Betti & F. Gagliardi & A. D'Agostino & L. Neri, 2025. "An R tool for computing and evaluating Fuzzy poverty indices: The package FuzzyPovertyR," Journal of Applied Statistics, Taylor & Francis Journals, vol. 52(15), pages 2958-2971, November.
    • Handle: RePEc:taf:japsta:v:52:y:2025:i:15:p:2958-2971
    DOI: 10.1080/02664763.2025.2481461
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