The Priestley–Chao estimator is a non-parametric derivative estimator related to kernel smoothing, but it is specifically used when the goal is to estimate changes in a function, rather than just its level.

Unlike the Nadaraya–Watson estimator, it does not aim to predict the value of the function
f(x) directly, but rather focuses on changes in the function’s behavior — for example, its derivative, which indicates upward or downward trends.