Quantile regression offers great flexibility in assessing covariate effects on event times, thereby attracting considerable interests in its applications in survival analysis. But currently available ...

Joe Whittaker, Chris Whitehead, Mark Somers, The Neglog Transformation and Quantile Regression for the Analysis of a Large Credit Scoring Database, Journal of the Royal Statistical Society.

One solution is to ditch the standard linear regression and replace it with quantile regression, which is less vulnerable to extreme data points. What’s the difference in these regressions?