The bias of Fisher information for large-n samples of dynamical curves is calculated, with clustering of degrees of freedom shown to reduce bias and improve reconstruction accuracy from the same data.
Entropy differential metric, distance and divergence measures in probability spaces: A unified approach,
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Fisher Information and Dynamical Sampling I
The bias of Fisher information for large-n samples of dynamical curves is calculated, with clustering of degrees of freedom shown to reduce bias and improve reconstruction accuracy from the same data.