Semiparametric median residual life model and inference |
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Authors: | Yanyuan Ma Guosheng Yin |
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Affiliation: | 1. Department of Statistics, Texas A&M University, College Station, TX 77843, USA;2. Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong |
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Abstract: | For randomly censored data, the authors propose a general class of semiparametric median residual life models. They incorporate covariates in a generalized linear form while leaving the baseline median residual life function completely unspecified. Despite the non‐identifiability of the survival function for a given median residual life function, a simple and natural procedure is proposed to estimate the regression parameters and the baseline median residual life function. The authors derive the asymptotic properties for the estimators, and demonstrate the numerical performance of the proposed method through simulation studies. The median residual life model can be easily generalized to model other quantiles, and the estimation method can also be applied to the mean residual life model. The Canadian Journal of Statistics 38: 665–679; 2010 © 2010 Statistical Society of Canada |
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Keywords: | Residual lifetime median regression survival function identifiability semiparametric model MSC 2000: Primary 62N01 secondary 62N02 |
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