High Quality Content by WIKIPEDIA articles! In information theory, the Renyi entropy, a generalisation of Shannon entropy, is one of a family of functionals for quantifying the diversity, uncertainty or randomness of a system. It is named after Alfred Renyi. Higher values of ?, approaching infinity, give a Renyi entropy which is increasingly determined by consideration of only the highest probability events. Lower values of ?, approaching zero, give a Renyi entropy which increasingly weights all possible events more equally, regardless of their probabilities. The intermediate case ?=1 gives the Shannon entropy, which has special properties. The Renyi entropies are important in ecology and statistics as indices of diversity.

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