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  2. Principle of maximum caliber - Wikipedia

    en.wikipedia.org/wiki/Principle_of_maximum_caliber

    The principle of maximum caliber (MaxCal) or maximum path entropy principle, suggested by E. T. Jaynes, [1] can be considered as a generalization of the principle of maximum entropy. It postulates that the most unbiased probability distribution of paths is the one that maximizes their Shannon entropy. This entropy of paths is sometimes called ...

  3. Maximal entropy random walk - Wikipedia

    en.wikipedia.org/wiki/Maximal_Entropy_Random_Walk

    To practically use such long sequences, after 1 we have to use 0, but there remains a freedom of choosing the probability of 0 after 0. Let us denote this probability by , then entropy coding would allow encoding a message using this chosen probability distribution. The stationary probability distribution of symbols for a given turns out to be

  4. Random walk - Wikipedia

    en.wikipedia.org/wiki/Random_walk

    Five eight-step random walks from a central point. Some paths appear shorter than eight steps where the route has doubled back on itself. (animated version)In mathematics, a random walk, sometimes known as a drunkard's walk, is a stochastic process that describes a path that consists of a succession of random steps on some mathematical space.

  5. Orders of magnitude (probability) - Wikipedia

    en.wikipedia.org/wiki/Orders_of_magnitude...

    1.4×10 −3: Probability of a human birth giving triplets or higher-order multiples [18] Probability of being dealt a full house in poker 1.9×10 −3: Probability of being dealt a flush in poker 2.7×10 −3: Probability of a random day of the year being your birthday (for all birthdays besides Feb. 29) 4×10 −3: Probability of being dealt ...

  6. Convergence of random variables - Wikipedia

    en.wikipedia.org/wiki/Convergence_of_random...

    In other words, if X n converges in probability to X sufficiently quickly (i.e. the above sequence of tail probabilities is summable for all ε > 0), then X n also converges almost surely to X. This is a direct implication from the Borel–Cantelli lemma. If S n is a sum of n real independent random variables:

  7. Bell diagonal state - Wikipedia

    en.wikipedia.org/wiki/Bell_diagonal_state

    where ,,, is a probability distribution. Since p 1 + p 2 + p 3 + p 4 = 1 {\displaystyle p_{1}+p_{2}+p_{3}+p_{4}=1} , a Bell diagonal state is determined by three real parameters. The maximum probability of a Bell diagonal state is defined as p m a x = max { p 1 , p 2 , p 3 , p 4 } {\displaystyle p_{max}=\max\{p_{1},p_{2},p_{3},p_{4}\}} .

  8. SBA loans approved for Louisiana businesses impacted by ...

    www.aol.com/news/sba-loans-approved-louisiana...

    (The Center Square) — Gov. Jeff Landry announced that the U.S. Small Business Administration has approved an Economic Injury Disaster Declaration to assist businesses impacted by the New Year's ...

  9. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    A probability distribution is not uniquely determined by the moments E[X n] = e nμ + ⁠ 1 / 2 ⁠ n 2 σ 2 for n ≥ 1. That is, there exist other distributions with the same set of moments. [4] In fact, there is a whole family of distributions with the same moments as the log-normal distribution. [citation needed]

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