Abstract
AbstractAs mentioned in Chapter 2, the mean residual life function is sensitive to outliers. In this chapter, as an alternative we consider the quantile residual life function, which is robust under any skewed distribution. We first review asymptotic theories of the quantile function and quantile residual life function, and derive the quantile residual life process as a Brownian bridge. We also discuss parametric and nonparametric inferences on the quantile residual life function for one-sample, two-sample, and regression settings.KeywordsSurvival FunctionResidual LifeQuantile FunctionBrownian BridgeResidual LifetimeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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