Search results
Results From The WOW.Com Content Network
The stable distribution family is also sometimes referred to as the Lévy alpha-stable distribution, after Paul Lévy, the first mathematician to have studied it. [ 1 ] [ 2 ] Of the four parameters defining the family, most attention has been focused on the stability parameter, α {\displaystyle \alpha } (see panel).
The counterpart of the stable distribution in this case is the geometric stable distribution Max-stability : here the operation is to take the maximum of a number of random variables. The counterpart of the stable distribution in this case is the generalized extreme value distribution , and the theory for this case is dealt with as extreme ...
The stable distribution family is also sometimes referred to as the Lévy alpha-stable distribution, after Paul Lévy, the first mathematician to have studied it. [ 2 ] Of the three parameters defining the distribution, the stability parameter α {\displaystyle \alpha } is most important.
This page was last edited on 14 September 2019, at 04:56 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.
An illustration of a gömböc. The problem was solved in 2006 by Gábor Domokos and Péter Várkonyi. Domokos met Arnold in 1995 at a major mathematics conference in Hamburg, where Arnold presented a plenary talk illustrating that most geometrical problems have four solutions or extremal points.
This page was last edited on 7 December 2016, at 21:06 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.
The multivariate stable distribution defines linear relations between stable distribution marginals. [clarification needed] In the same way as for the univariate case, the distribution is defined in terms of its characteristic function. The multivariate stable distribution can also be thought as an extension of the multivariate normal ...
Degenerate distribution; Delaporte distribution; Dirichlet-multinomial distribution; Discrete uniform distribution; Discrete Weibull distribution; Discrete-stable distribution; Displaced Poisson distribution; Dyadic distribution