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Bootstrap approach to the multi-sample test of means with imprecise data

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  • Gil, Maria Angeles
  • Montenegro, Manuel
  • Gonzalez-Rodriguez, Gil
  • Colubi, Ana
  • Rosa Casals, Maria

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  • Gil, Maria Angeles & Montenegro, Manuel & Gonzalez-Rodriguez, Gil & Colubi, Ana & Rosa Casals, Maria, 2006. "Bootstrap approach to the multi-sample test of means with imprecise data," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 148-162, November.
    • Handle: RePEc:eee:csdana:v:51:y:2006:i:1:p:148-162
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    References listed on IDEAS

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    1. Volker Krätschmer, 2004. "Probability theory in fuzzy sample spaces," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 60(2), pages 167-189, September.
    2. Lopez-Diaz, Miguel & Ralescu, Dan A., 2006. "Tools for fuzzy random variables: Embeddings and measurabilities," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 109-114, November.
    3. Manuel Montenegro & Ana Colubi & María Rosa Casals & María Ángeles Gil, 2004. "Asymptotic and Bootstrap techniques for testing the expected value of a fuzzy random variable," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 59(1), pages 31-49, February.
    4. Cuevas, Antonio & Febrero, Manuel & Fraiman, Ricardo, 2004. "An anova test for functional data," Computational Statistics & Data Analysis, Elsevier, vol. 47(1), pages 111-122, August.
    5. Gonzalez-Rodriguez, Gil & Colubi, Ana & Angeles Gil, Maria, 2006. "A fuzzy representation of random variables: An operational tool in exploratory analysis and hypothesis testing," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 163-176, November.
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    Cited by:

    1. Ana Colubi & Renato Coppi & Pierpaolo D’urso & Maria angeles Gil, 2007. "Statistics with fuzzy random variables," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 277-303.
    2. Massimo Aria & Antonio D’Ambrosio & Carmela Iorio & Roberta Siciliano & Valentina Cozza, 2020. "Dynamic recursive tree-based partitioning for malignant melanoma identification in skin lesion dermoscopic images," Statistical Papers, Springer, vol. 61(4), pages 1645-1661, August.
    3. A. Blanco-Fernández & A. Ramos-Guajardo & A. Colubi, 2013. "Fuzzy representations of real-valued random variables: applications to exploratory and inferential studies," METRON, Springer;Sapienza Università di Roma, vol. 71(3), pages 245-259, November.
    4. Elena Fernández & Ana Colubi & Gil González-Rodríguez & Soledad Anadón, 2012. "Integrating statistical information concerning historical floods: ranking and interval return period estimation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 62(2), pages 459-483, June.
    5. Lopez-Diaz, Miguel & Ralescu, Dan A., 2006. "Tools for fuzzy random variables: Embeddings and measurabilities," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 109-114, November.
    6. Colubi, Ana & Gonzalez-Rodriguez, Gil, 2007. "Triangular fuzzification of random variables and power of distribution tests: Empirical discussion," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4742-4750, May.
    7. Choirat, Christine & Seri, Raffaello, 2014. "Bootstrap confidence sets for the Aumann mean of a random closed set," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 803-817.
    8. Pierpaolo D’Urso & María Ángeles Gil, 2017. "Fuzzy data analysis and classification," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(4), pages 645-657, December.
    9. Gholamreza Hesamian, 2016. "One-way ANOVA based on interval information," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(11), pages 2682-2690, August.
    10. González-Rodríguez, Gil & Colubi, Ana & Gil, María Ángeles, 2012. "Fuzzy data treated as functional data: A one-way ANOVA test approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 943-955.
    11. María Casals & Norberto Corral & María Gil & María López & María Lubiano & Manuel Montenegro & Gloria Naval & Antonia Salas, 2013. "Bertoluzza et al.’s metric as a basis for analyzing fuzzy data," METRON, Springer;Sapienza Università di Roma, vol. 71(3), pages 307-322, November.
    12. Mohammad Ghasem Akbari & Gholamreza Hesamian, 2017. "Record value based on intuitionistic fuzzy random variables," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(15), pages 3305-3315, November.
    13. Ramos-Guajardo, Ana Belén & Lubiano, María Asunción, 2012. "K-sample tests for equality of variances of random fuzzy sets," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 956-966.
    14. Ana Ramos-Guajardo & Ana Colubi & Gil González-Rodríguez & María Gil, 2010. "One-sample tests for a generalized Fréchet variance of a fuzzy random variable," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 71(2), pages 185-202, March.
    15. Coppi, Renato & Gil, Maria A. & Kiers, Henk A.L., 2006. "The fuzzy approach to statistical analysis," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 1-14, November.
    16. Lubiano, María Asunción & Montenegro, Manuel & Sinova, Beatriz & de la Rosa de Sáa, Sara & Gil, María Ángeles, 2016. "Hypothesis testing for means in connection with fuzzy rating scale-based data: algorithms and applications," European Journal of Operational Research, Elsevier, vol. 251(3), pages 918-929.
    17. Gonzalez-Rodriguez, Gil & Colubi, Ana & Angeles Gil, Maria, 2006. "A fuzzy representation of random variables: An operational tool in exploratory analysis and hypothesis testing," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 163-176, November.

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