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  2. Sample entropy - Wikipedia

    en.wikipedia.org/wiki/Sample_entropy

    Like approximate entropy (ApEn), Sample entropy (SampEn) is a measure of complexity. [1] But it does not include self-similar patterns as ApEn does. For a given embedding dimension, tolerance and number of data points, SampEn is the negative natural logarithm of the probability that if two sets of simultaneous data points of length have distance < then two sets of simultaneous data points of ...

  3. Entropy (statistical thermodynamics) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(statistical...

    Ludwig Boltzmann defined entropy as a measure of the number of possible microscopic states (microstates) of a system in thermodynamic equilibrium, consistent with its macroscopic thermodynamic properties, which constitute the macrostate of the system. A useful illustration is the example of a sample of gas contained in a container.

  4. List of statistics articles - Wikipedia

    en.wikipedia.org/wiki/List_of_statistics_articles

    Maximum entropy classifier – redirects to Logistic regression; Maximum-entropy Markov model; Maximum entropy method – redirects to Principle of maximum entropy; Maximum entropy probability distribution; Maximum entropy spectral estimation; Maximum likelihood; Maximum likelihood sequence estimation; Maximum parsimony; Maximum spacing estimation

  5. Entropy estimation - Wikipedia

    en.wikipedia.org/wiki/Entropy_estimation

    A new approach to the problem of entropy evaluation is to compare the expected entropy of a sample of random sequence with the calculated entropy of the sample. The method gives very accurate results, but it is limited to calculations of random sequences modeled as Markov chains of the first order with small values of bias and correlations ...

  6. Entropy (information theory) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(information_theory)

    The concept of information entropy was introduced by Claude Shannon in his 1948 paper "A Mathematical Theory of Communication", [2] [3] and is also referred to as Shannon entropy. Shannon's theory defines a data communication system composed of three elements: a source of data, a communication channel, and a receiver. The "fundamental problem ...

  7. Mutual information - Wikipedia

    en.wikipedia.org/wiki/Mutual_information

    The joint information is equal to the mutual information plus the sum of all the marginal information (negative of the marginal entropies) for each particle coordinate. Boltzmann's assumption amounts to ignoring the mutual information in the calculation of entropy, which yields the thermodynamic entropy (divided by the Boltzmann constant).

  8. Senators raise concern about Chinese influence on Panama ...

    www.aol.com/news/senators-raise-concern-chinese...

    A bipartisan group of U.S. senators on Tuesday expressed alarm at China's influence on the Panama Canal, which President Donald Trump has vowed the United States would take back. "Chinese ...

  9. Kullback–Leibler divergence - Wikipedia

    en.wikipedia.org/wiki/Kullback–Leibler_divergence

    where (,) is the cross entropy of Q relative to P and () is the entropy of P (which is the same as the cross-entropy of P with itself). The relative entropy D KL ( P ∥ Q ) {\displaystyle D_{\text{KL}}(P\parallel Q)} can be thought of geometrically as a statistical distance , a measure of how far the distribution Q is from the distribution P .