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Weibull distribution
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===Shannon entropy=== The [[entropy (information theory)|information entropy]] is given by<ref>{{Cite journal |last1=Cho |first1=Youngseuk |last2=Sun |first2=Hokeun |last3=Lee |first3=Kyeongjun |date=5 January 2015 |title=Estimating the Entropy of a Weibull Distribution under Generalized Progressive Hybrid Censoring |journal=Entropy |language=en |volume=17 |issue=1 |pages=102–122 |doi=10.3390/e17010102 |doi-access=free |bibcode=2015Entrp..17..102C |issn=1099-4300}}</ref> :<math> H(\lambda,k) = \gamma\left(1 - \frac{1}{k}\right) + \ln\left(\frac{\lambda}{k}\right) + 1 </math> where <math>\gamma</math> is the [[Euler–Mascheroni constant]]. The Weibull distribution is the [[maximum entropy distribution]] for a non-negative real random variate with a fixed [[expected value]] of ''x''<sup>''k''</sup> equal to ''λ''<sup>''k''</sup> and a fixed expected value of ln(''x''<sup>''k''</sup>) equal to ln(''λ''<sup>''k''</sup>) − <math>\gamma</math>.
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