A central limit theorem for the Hellinger loss of Grenander type estimators
classification
🧮 math.ST
stat.TH
keywords
hellingerlambdalosscentralestimatorsgrenanderlimitmonotone
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We consider Grenander type estimators for a monotone function $\lambda:[0,1]\to\mathbb{R}$, obtained as the slope of a concave (convex) estimate of the primitive of $\lambda$. Our main result is a central limit theorem for the Hellinger loss, which applies to statistical models that satisfy the setup in Durot (2007). This includes estimation of a monotone density, for which the limiting variance of the Hellinger loss turns out to be independent of $\lambda$.
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