Probability in the Engineering and Informational Sciences · 2018 · 29 citations · 20 references
Natural SciencesMathematicsInformation TheoryProbability TheoryStochastic ProcessesEntropyInformation MeasuresProbability DistributionsInformation EntropyResidual EntropyShannon Entropy
Abstract The Shannon entropy based on the probability density function is a key information measure with applications in different areas. Some alternative information measures have been proposed in the literature. Two relevant ones are the cumulative residual entropy (based on the survival function) and the cumulative past entropy (based on the distribution function). Recently, some extensions of these measures have been proposed. Here, we obtain some properties for the generalized cumulative past entropy. In particular, we prove that it determines the underlying distribution. We also study this measure in coherent systems and a closely related generalized past cumulative Kerridge inaccuracy measure.
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A Mathematical Theory of Communication
Claude E. Shannon · Bell System Technical Journal · 1948 · 80.7K citations
Mathematical Theory of Reliability
A. P. Basu, Richard E. Barlow, Frank Proschan · Econometrica · 1966 · 2.7K citations
Cumulative Residual Entropy: A New Measure of Information
Murali Rao, Yu Chen, Baba C. Vemuri et al. · IEEE Transactions on Information Theory · 2004 · 613 citations