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  2. Probabilistic programming - Wikipedia

    en.wikipedia.org/wiki/Probabilistic_programming

    Reasoning about variables as probability distributions causes difficulties for novice programmers, but these difficulties can be addressed through use of Bayesian network visualizations and graphs of variable distributions embedded within the source code editor.

  3. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The Birnbaum–Saunders distribution, also known as the fatigue life distribution, is a probability distribution used extensively in reliability applications to model failure times. The chi distribution. The noncentral chi distribution; The chi-squared distribution, which is the sum of the squares of n independent Gaussian random variables.

  4. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    A discrete probability distribution is the probability distribution of a random variable that can take on only a countable number of values [15] (almost surely) [16] which means that the probability of any event can be expressed as a (finite or countably infinite) sum: = (=), where is a countable set with () =.

  5. Panjer recursion - Wikipedia

    en.wikipedia.org/wiki/Panjer_recursion

    The number of claims N is a random variable, which is said to have a "claim number distribution", and which can take values 0, 1, 2, .... etc.. For the "Panjer recursion", the probability distribution of N has to be a member of the Panjer class, otherwise known as the (a,b,0) class of distributions. This class consists of all counting random ...

  6. Kernel embedding of distributions - Wikipedia

    en.wikipedia.org/wiki/Kernel_embedding_of...

    The goal of domain adaptation is the formulation of learning algorithms which generalize well when the training and test data have different distributions. Given training examples {(,)} = and a test set {(,)} = where the are unknown, three types of differences are commonly assumed between the distribution of the training examples (,) and the ...

  7. Stable distribution - Wikipedia

    en.wikipedia.org/wiki/Stable_distribution

    The distributions have undefined variance for <, and undefined mean for . The importance of stable probability distributions is that they are "attractors" for properly normed sums of independent and identically distributed random variables. The normal distribution defines a family of stable distributions.

  8. Estimation of distribution algorithm - Wikipedia

    en.wikipedia.org/wiki/Estimation_of_distribution...

    Estimation of distribution algorithm. For each iteration i, a random draw is performed for a population P in a distribution PDu. The distribution parameters PDe are then estimated using the selected points PS. The illustrated example optimizes a continuous objective function f(X) with a unique optimum O.

  9. Stochastic ordering - Wikipedia

    en.wikipedia.org/wiki/Stochastic_ordering

    Downward-lexicographic dominance, denoted , means that has a larger probability than of returning the best outcome, or both and have the same probability to return the best outcome but has a larger probability than of returning the second-best best outcome, etc. Upward-lexicographic dominance is defined analogously based on the probability to ...