Quantile regression with censored data using generalized L1minimization

• We propose a way to estimate a parametric quantile function when the dependent variable, e.g. the survival time, is censored. We discuss one way to do this, transforming the problem of finding the p-quantile for the true, uncensored, survival times into a problem of finding the q-quantile for the observed, censored, times. The q-value involves the distribution of the censoring times, which is unknown. The estimation of the quantile function is done using the asymmetric L1 technique with weights involving local Kaplan-Meier estimates of the distribution of the censoring limit.

Ämnesord

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)

NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)

Nyckelord

Quantile regression

L1 minimization

Right censoring

Kaplan-Meier estimator

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