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  2. 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.

  3. 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.

  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. Bayesian hierarchical modeling - Wikipedia

    en.wikipedia.org/wiki/Bayesian_hierarchical_modeling

    The parameter is called the hyperparameter, while its distribution given by (,) is an example of a hyperprior distribution. The notation of the distribution of Y changes as another parameter is added, i.e. Y ∣ θ , μ ∼ N ( θ , 1 ) {\displaystyle Y\mid \theta ,\mu \sim N(\theta ,1)} .

  6. Complex random variable - Wikipedia

    en.wikipedia.org/wiki/Complex_random_variable

    Another example of a complex random variable is the uniform distribution over the filled unit circle, i.e. the set {| |}. This random variable is an example of a complex random variable for which the probability density function is defined. The density function is shown as the yellow disk and dark blue base in the following figure.

  7. 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 ...

  8. Elliptical distribution - Wikipedia

    en.wikipedia.org/wiki/Elliptical_distribution

    In probability and statistics, an elliptical distribution is any member of a broad family of probability distributions that generalize the multivariate normal distribution. Intuitively, in the simplified two and three dimensional case, the joint distribution forms an ellipse and an ellipsoid , respectively, in iso-density plots.

  9. List of probability topics - Wikipedia

    en.wikipedia.org/wiki/List_of_probability_topics

    This is a list of probability topics. It overlaps with the (alphabetical) list of statistical topics. There are also the outline of probability and catalog of articles in probability theory. For distributions, see List of probability distributions. For journals, see list of probability journals.