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...a '''mixture''' is a probabilistic combination of two or more probability distributions.<ref>{{Cite journal|last1=Heidari|first1=Hadi|last2=Arabi|first2=Mazdak|las ...ibution]] from some existing ones, as in a [[mixture distribution]] or a [[compound distribution]]. Here a major problem often is to derive the properties of t ...

{{Short description|Probability distribution}} ...ixture''' with mixing probability density <math>g</math> is the continuous probability distribution of a random variable <math>Y</math> of the form ...

{{Short description|1=Overview of and topical guide to probability}} {{Probability topics sidebar}} ...

{{Short description|Probability distribution}} {{Probability distribution | ...

{{Short description|Discrete probability distribution}} {{Probability distribution| ...

{{Short description|Power series derived from a discrete probability distribution}} ...ct description of the sequence of probabilities Pr(''X'' = ''i'') in the [[probability mass function]] for a [[random variable]] ''X'', and to make available the ...

{{Short description|Aspect of probability theory}} In [[probability theory]], a '''compound Poisson distribution''' is the [[probability distribution]] of the sum of a number of [[independent identically-distribu ...

...n. The various moments form one set of values by which the properties of a probability distribution can be usefully characterized. Central moments are used in pre Sets of central moments can be defined for both univariate and multivariate distributions. ...

*[[Stability (probability)]], a property of probability distributions **[[Thermal stability]] of a chemical compound ...

In the [[mathematics]] of [[probability]], a [[stochastic process]] is a random [[function (mathematics)|function]] ...re the domain has some [[symmetry]] and the finite-dimensional probability distributions also have that symmetry. Special cases include [[stationary process]]es, al ...

...al cumulance''' is a generalization to [[cumulant]]s of the [[law of total probability]], the [[law of total expectation]], and the [[law of total variance]]. It ===Cumulants of compound Poisson random variables=== ...

{{short description|Stochastic process in probability theory}} ...in different time intervals of the same length have identical probability distributions. A Lévy process may thus be viewed as the continuous-time analog of a [[ran ...

{{Short description|Aspect of probability and statistics}} ...bset]] of a [[indexed family|collection]] of [[random variable]]s is the [[probability distribution]] of the variables contained in the subset. It gives the proba ...

...scription|In statistics and probability theory, set of outcomes to which a probability is assigned}} {{Probability fundamentals}} ...

The [[Information theory|mathematical theory of information]] is based on [[probability theory]] and [[statistics]], and measures information with several '''quant where <math>p(m) = \mathrm{Pr}(M=m)</math> is the probability that message <math>m</math> is chosen from all possible choices in the mess ...

{{Short description|Discrete probability distribution}} {{Probability distribution | ...

{{Short description|Type of probability distribution}} {{See also|Mixture model|Compound probability distribution}} ...

Many [[probability distribution]]s that are important in theory or applications have been give ==Discrete distributions== ...

{{Short description|Probability distribution}} {{Probability distribution ...

{{Short description|Concept in probability theory}} In [[Bayesian probability]] theory, if, given a [[likelihood function]] ...