Robust and Efficient Parametric Estimation for Censored Survival Data
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DOI: 10.1007/s10463-005-0004-x
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- Cao, Ricardo & Cuevas, Antonio & Fraiman, Ricardo, 1995. "Minimum distance density-based estimation," Computational Statistics & Data Analysis, Elsevier, vol. 20(6), pages 611-631, December.
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Cited by:
- Adhidev Biswas & Suman Majumder & Pratim Guha Niyogi & Ayanendranath Basu, 2021. "A Weighted Likelihood Approach to Problems in Survival Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 466-492, November.
- Pierre‐Yves Deléamont & Elvezio Ronchetti, 2022. "Robust inference with censored survival data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1496-1533, December.
- Abhik Ghosh, 2022. "Robust parametric inference for finite Markov chains," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 118-147, March.
- R. Bajorunaite & V. Brazauskas, 2008. "Method of trimmed moments for robust fitting of parametric failure time models," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 341-360.
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Keywords
Density power divergence; Kaplan–Meier; L 2 -estimator; M-estimator;All these keywords.
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