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In Bayesian statistics a prior distribution formalizes information or knowledge (often subjective), available before a sample is seen, in the form of a probability distribution. A distribution with large spread is used when little is known about the parameter(s), while a more narrow prior distribution represents a greater degree of information.
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Priors in Shannon and Rényi entropies
[Note: Cross-posted at Math StackExchange]
I am new to information theory and currently working with Shannon and Rényi entropies. Given the pdf $p_{\theta}(x)$ of a random variable $x$, that is para …