Abstract
Estimation of bivariate survival function for right censored data has a long history. After providing a brief review of the existing literature, we introduce a class of novel estimators for this problem. We provide numerical evidence of the superiority of our estimators over existing estimators. Applicability of these estimators and related bootstrap inference are illustrated using a real life data set.
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Acknowledgement
Zheng received research support from the Fundamental Research Funds for the Central Universities, China, SWJTU12ZT15. Datta’s research was supported by grants from the United States National Science Foundation (DMS-0706965) and United States National Security Agency (H98230-11-1-0168). We thank an anonymous referee for suggesting a number of corrections to an earlier draft.
Thank you Hira for being a great teacher, friend and colleague! Over the years, I have enjoyed and learned from various interactions with you. Wish you many more healthy and productive years to come! Hope you enjoy reading this paper. (S.D.)
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Zheng, H., Yang, G., Data, S. (2014). A Note on Nonparametric Estimation of a Bivariate Survival Function Under Right Censoring. In: Lahiri, S., Schick, A., SenGupta, A., Sriram, T. (eds) Contemporary Developments in Statistical Theory. Springer Proceedings in Mathematics & Statistics, vol 68. Springer, Cham. https://doi.org/10.1007/978-3-319-02651-0_5
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DOI: https://doi.org/10.1007/978-3-319-02651-0_5
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