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Generalized extreme value distribution; Generalized gamma distribution; Generalized integer gamma distribution; Generalized inverse Gaussian distribution; Generalized logistic distribution; Generalized multivariate log-gamma distribution; Generalized normal distribution; Generalized Pareto distribution; Geometric stable distribution; Gompertz ...
The Boltzmann distribution, a discrete distribution important in statistical physics which describes the probabilities of the various discrete energy levels of a system in thermal equilibrium. It has a continuous analogue. Special cases include: The Gibbs distribution; The Maxwell–Boltzmann distribution; The Borel distribution
In probability theory, statistics, and machine learning, the continuous Bernoulli distribution [1] [2] [3] is a family of continuous probability distributions parameterized by a single shape parameter (,), defined on the unit interval [,], by:
An absolutely continuous random variable is a random variable whose probability distribution is absolutely continuous. There are many examples of absolutely continuous probability distributions: normal, uniform, chi-squared, and others.
In probability theory and statistics, the continuous uniform distributions or rectangular distributions are a family of symmetric probability distributions. Such a distribution describes an experiment where there is an arbitrary outcome that lies between certain bounds. [ 1 ]
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As the logistic distribution, which can be solved analytically, is similar to the normal distribution, it can be used instead. The blue picture illustrates an example of fitting the logistic distribution to ranked October rainfalls—that are almost normally distributed—and it shows the 90% confidence belt based on the binomial distribution.
In probability and statistics, the reciprocal distribution, also known as the log-uniform distribution, is a continuous probability distribution. It is characterised by its probability density function , within the support of the distribution, being proportional to the reciprocal of the variable.