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Given a sample of size $n$ from a distribution $P_\lambda$, one wants to estimate a functional $\psi(\lambda)$ of the (typically infinite-dimensional) parameter $\lambda$. Lower bounds on the performance of estimators can be based on the concept of a differentiable functional $P_\lambda \rightarrow \psi(\lambda)$. In this paper we relate a suitable definition of differentiable functional to differentiability of $\alpha \rightarrow dP^{1/2}_\lambda$ and $\lambda \rightarrow \psi(\lambda)$. Moreover, we show that regular estimability of a functional implies its differentiability.
mixture model, truncation, Convolution theorem, asymptotic efficiency, semi-parametric model, information operator, censoring, 62G05, efficient information, 62G20
mixture model, truncation, Convolution theorem, asymptotic efficiency, semi-parametric model, information operator, censoring, 62G05, efficient information, 62G20
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 136 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |