A note on breaking ties among sample medians

Abstract: Given samples $x_1,\cdots,x_n$, it is well known that any sample median value (not necessarily unique) minimizes the absolute loss $\sum_{i=1}ⁿ |q-x_i|$. Interestingly, we show that the minimizer of the loss $\sum_{i=1}<sup>n|q-x_i|<sup>{1+\epsilon}$ exhibits a singular perturbation behaviour that provides a unique definition for the sample median as $\epsilon \rightarrow 0$. This definition is the unique point among all candidate median values that balances the $logarithmic$ moment of the empirical distribution. The result generalizes directly to breaking ties among sample quantiles when the quantile regression loss is modified in the same way.