Online monotone density estimation and log-optimal calibration

ArXi:2602.08927v2 Announce Type: replace-cross We study the problem of online monotone density estimation, where density estimators must be constructed in a predictable manner from sequentially observed data. We propose two online estimators: an online analogue of the classical Grenander estimator, and an expert aggregation estimator inspired by exponential weighting methods from the online learning literature.