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- In the mathematical theory of probability, the '''Heyde theorem''' is the [[characterization (mathematics)|chara ...<math>\xi_j, j = 1, 2, \ldots, n, n \ge 2</math> be [[independence (probability theory)|independent]] random variables. Let <math>\alpha_j, \beta_j</math>& ...1 KB (191 words) - 04:27, 13 March 2024
- ...alently the limiting behavior of distribution’s [[Characteristic function (probability theory)|characteristic function]]. ...4/aos/1176348248|doi-access=free}}</ref> if its [[Characteristic function (probability theory)|characteristic function]] satisfies ...2 KB (268 words) - 01:44, 29 August 2020
- * A has a higher probability than B of receiving the best outcome. ...ave an equal probability of receiving the best outcome, but A has a higher probability of receiving the 2nd-best outcome. ...5 KB (758 words) - 22:21, 7 August 2023
- ...goes to 1 as ''n'' goes to infinity, i.e. the probability of the [[Event (probability theory)|event]] occurring can be made as close to 1 as desired by making '' ...en when the number of nodes is very large, the algorithm is correct with a probability that is very near 1. This fact is expressed shortly by saying that the algo ...3 KB (429 words) - 02:19, 9 January 2025
- ...nce|inverse problems]] on [[function space]]s for which a Gaussian [[prior probability|Bayesian prior]] is an inappropriate model. The construction of a Besov me ...\xi_{n} |^{p} )</math>. Informally, <math>u</math> can be said to have a probability density function proportional to <math>\exp (- \tfrac{\kappa}{2} \| u \|_{X ...6 KB (850 words) - 10:24, 28 August 2024
- ===Problems with Metropolis–Hastings=== ...ses, one uses a Gaussian distribution centered on the current point in the probability space, of the form <math>Q(x'; x^t)=\mathcal{N}(x^t;\sigma^2 I) \,</math>. ...7 KB (1,122 words) - 22:13, 19 March 2024
- ...of a probability distribution''' accordingly states that it is the only [[probability distribution]] that satisfies specified conditions. More precisely, the mod ...>. By characterizations of probability distributions we understand general problems of description of some set <math> \mathcal{C}</math> in the space <math> \m ...7 KB (1,023 words) - 06:27, 2 July 2021
- {{Short description|Theorem in probability theory}} ...rnal|last=Rukhin A. L.|date=1970|title=Certain statistical and probability problems on groups|journal=Trudy Mat. Inst. Steklov|volume=111|pages=52–109}}</ref>< ...3 KB (471 words) - 21:47, 20 February 2025
- {{Short description|Probability problem}} The '''Newton–Pepys problem''' is a [[probability]] problem concerning the probability of throwing sixes from a certain number of dice.<ref name="wolfram">{{MathW ...5 KB (843 words) - 18:37, 20 December 2024
- ...entary event|complement]] of failure <math>(\text{Reliability} = 1 - \text{Probability of Failure})</math>. The failure occurs when the total applied load is larg ...and resistances are explicit and have their own independent function, the probability of failure could be formulated as follows.<ref name=":0" /><ref name=":1" / ...4 KB (514 words) - 07:32, 6 January 2025
- ...processes where certain constraints need to be satisfied with a specified probability. ...[probability]] and confidence levels to handle uncertainty in optimization problems. It distinguishes between single and joint chance constraints: ...6 KB (746 words) - 07:24, 15 December 2024
- ...simpler subsets. In [[probability theory]] it is the approximation of one probability distribution by another. ...and not ''P''. One straightforward way to compute an ε-net with high probability is to take a sufficient number of random points, where the number of random ...5 KB (717 words) - 11:25, 26 April 2024
- ==Related problems== Similar problems describe the [[bipartite graph|degree sequence]]s of [[bipartite graph|simp ...4 KB (588 words) - 01:41, 22 February 2025
- In [[probability theory]] and [[statistics]], the '''generalized multivariate log-gamma (G-M ==Joint probability density function== ...5 KB (725 words) - 21:02, 9 December 2016
- ...tant. It is a [[randomized algorithm]] whose running time is O(''n'') with probability close to 1. The protocol was developed by [[Jeff Edmonds]] and [[Kirk Pruhs The algorithm guarantees that, with high probability, each partner receives at least half of one of his candidate pieces, which ...9 KB (1,538 words) - 08:57, 23 July 2023
- ...m that succeeds with high probability (having a polynomially small failure probability).{{r|yv}} If so, this would be optimal, as connected components can be cons ...l complexity class [[NC (complexity)|NC<sup>1</sup>]] does not contain all problems in [[polynomial time]], which would be a significant advance on current kno ...4 KB (518 words) - 00:29, 13 January 2025
- {{Short description|Continuous probability distribution}} {{Probability distribution | ...8 KB (1,111 words) - 23:04, 24 February 2025
- ...n percolation |url=https://www.jstor.org/stable/2652916 |journal=Annals of Probability |volume=29 |issue=1 |pages=123–126 |doi=10.1214/aop/1008956324 |jstor=26529 ...upper bunk and their corresponding edges in the lower bunk share the same probability. The probabilities assigned to the posts can be arbitrary. ...7 KB (926 words) - 16:54, 7 January 2025
- ...machine in polynomial time, upon measuring the first qubit, with an error probability of at most 1/poly(n) for all instances.<ref name="shorjordan2008" /> ...ty)|BPP]], [[BQP]], and [[RP (complexity)|RP]] are agnostic to the precise probability gap, because any polynomial acceptance gap can be ''amplified'' to a fixed ...7 KB (1,007 words) - 22:27, 1 March 2025
- ...le:Warehouse md17.jpg|thumb|Regenerative processes have been used to model problems in inventory control. The inventory in a warehouse such as this one decreas ...tions | doi = 10.1016/B978-0-12-375686-2.00003-0 | title = Introduction to Probability Models | pages = 421–641 | year = 2010 | isbn = 9780123756862 }}</ref> This ...5 KB (711 words) - 07:35, 26 February 2024