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Limiting probabilities: The probability that a continuous-time Markov chain will be in state j at time t often converges to a limiting value which is independent of the intial state. We call this value Pj where Pj is equal to: ( λ 0 ... [100%] 2023-11-19 [Mathematics stubs] [Probability]...
Geometric probabilities: Probabilities of events related to the relative location of geometric figures placed at random on a plane or in a space. The simplest example may be stated as follows: A point is "thrown" at random into a planar domain $A ... (Mathematics) [100%] 2023-11-20
Imprecise Probabilities: It has been argued that imprecise probabilities are a natural and intuitive way of overcoming some of the issues with orthodox precise probabilities. Models of this type have a long pedigree, and interest in such models has been growing in ... (Philosophy) [100%] 2022-02-20
Transition probabilities: The probabilities of transition of a Markov chain $ \xi ( t) $ from a state $ i $ into a state $ j $ in a time interval $ [ s, t] $: $$ p _ {ij} ( s, t) = {\mathsf P} \{ \xi ( t) = j \mid \xi ( s) = i \} ,\ s< t ... (Mathematics) [100%] 2023-11-16
Contract bridge probabilities: In the game of bridge mathematical probabilities play a significant role. Different declarer play strategies lead to success depending on the distribution of opponent's cards. (Mathematical probabilities in the game of bridge) [81%] 2023-11-09 [Contract bridge probabilities]
Upper and lower probabilities: Upper and lower probabilities are representations of imprecise probability. Whereas probability theory uses a single number, the probability, to describe how likely an event is to occur, this method uses two numbers: the upper probability of the event and the ... [70%] 2023-12-28 [Exotic probabilities] [Probability bounds analysis]...
Matrix of transition probabilities: The matrix $ P _ {t} = \| p _ {ij} ( t) \| $ of transition probabilities in time $ t $ for a homogeneous Markov chain $ \xi ( t) $ with at most a countable set of states $ S $: $$ p _ {ij} ( t) = {\mathsf P} \{ \xi ( t) = j ... (Mathematics) [70%] 2023-10-29