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Rejoinder on: Nonparametric estimation in mixture cure models with covariates

Author

Listed:
  • Ana López-Cheda

    (University of A Coruña)

  • Yingwei Peng

    (Queen’s University)

  • María Amalia Jácome

    (University of A Coruña)

Abstract

No abstract is available for this item.

Suggested Citation

  • Ana López-Cheda & Yingwei Peng & María Amalia Jácome, 2023. "Rejoinder on: Nonparametric estimation in mixture cure models with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(2), pages 513-520, June.
    • Handle: RePEc:spr:testjl:v:32:y:2023:i:2:d:10.1007_s11749-023-00871-0
    DOI: 10.1007/s11749-023-00871-0
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    References listed on IDEAS

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    1. Qingli Dong & Yingwei Peng & Peizhi Li, 2022. "Time to delisted status for listed firms in Chinese stock markets: An analysis using a mixture cure model with time-varying covariates," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(10), pages 2358-2369, October.
    2. Jianping Li & Mingxi Liu & Cheng Few Lee & Dengsheng Wu, 2020. "Support Vector Machines Based Methodology for Credit Risk Analysis," World Scientific Book Chapters, in: Cheng Few Lee & John C Lee (ed.), HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING, chapter 20, pages 791-822, World Scientific Publishing Co. Pte. Ltd..
    3. Peizhi Li & Yingwei Peng & Ping Jiang & Qingli Dong, 2020. "A support vector machine based semiparametric mixture cure model," Computational Statistics, Springer, vol. 35(3), pages 931-945, September.
    4. Lore Dirick & Tony Bellotti & Gerda Claeskens & Bart Baesens, 2019. "Macro-Economic Factors in Credit Risk Calculations: Including Time-Varying Covariates in Mixture Cure Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 40-53, January.
    5. Yuanshan Wu & Guosheng Yin, 2017. "Multiple imputation for cure rate quantile regression with censored data," Biometrics, The International Biometric Society, vol. 73(1), pages 94-103, March.
    6. Lopez-Cheda, Ana & Cao, Ricardo & Jacome, Amalia & Van Keilegom, Ingrid, 2017. "Nonparametric incidence estimation and bootstrap bandwidth selection in mixture cure models," LIDAM Reprints ISBA 2017001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Yuanshan Wu & Guosheng Yin, 2013. "Cure Rate Quantile Regression for Censored Data With a Survival Fraction," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(504), pages 1517-1531, December.
    8. López-Cheda, Ana & Cao, Ricardo & Jácome, M. Amalia & Van Keilegom, Ingrid, 2017. "Nonparametric incidence estimation and bootstrap bandwidth selection in mixture cure models," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 144-165.
    9. Han-Ying Liang & Jacobo Uña-Álvarez & María Iglesias-Pérez, 2012. "Asymptotic properties of conditional distribution estimator with truncated, censored and dependent data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(4), pages 790-810, December.
    10. U U Müller & I Van Keilegom, 2019. "Goodness-of-fit tests for the cure rate in a mixture cure model," Biometrika, Biometrika Trust, vol. 106(1), pages 211-227.
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