2018
DOI: 10.1016/j.jmva.2018.08.003
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Representation of multivariate Bernoulli distributions with a given set of specified moments

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Cited by 20 publications
(32 citation statements)
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“…The class has 100 ray densities that we can find analitically and we found that all ray densities have different correlations. The bounds for the all moments of the distributions in the class are reached on the ray densities as proved in [9]. In this case the bounds for the second order moment and correlation are analytical, as proved in Section 3.1.1.…”
Section: Scenario 1: P = 03%mentioning
confidence: 87%
See 1 more Smart Citation
“…The class has 100 ray densities that we can find analitically and we found that all ray densities have different correlations. The bounds for the all moments of the distributions in the class are reached on the ray densities as proved in [9]. In this case the bounds for the second order moment and correlation are analytical, as proved in Section 3.1.1.…”
Section: Scenario 1: P = 03%mentioning
confidence: 87%
“…We build on the results in [9], where the authors represent the Fréchet class of multivariate d-dimensional Bernoulli distributions with given margins and/or pre-specified moments as the points of a convex hull. The generators of the convex hull are mass functions in the class and they can be explicitly found.…”
Section: Exchangeable Bernoulli Generatorsmentioning
confidence: 99%
“…A proof of (2) can be found in the Appendix. See also [14]. Because blockages are uniformly distributed over A, the probability that a given blockage lands in a i is equal to a i /A, and hence the probability it is outside a i is 1 − a i /A.…”
Section: Sinr Outage Analysismentioning
confidence: 99%
“…By substituting (15) and (16) into (14) and solving for E[B 1 B 2 ], E[B 1 B 2 ] = p 1 p 2 + ρ √ p 1 p 2 q 1 q 2 = p 1 p 2 + ρh.…”
Section: Appendixmentioning
confidence: 99%
“…Then, σ (M) = A −1 π (M) . Fontana and Semeraro [10] proposed a procedure based on this representation to construct a valid multivariate Bernoulli distribution for given marginal distributions, p i 's, and a correlation matrix, T = {τ i, j } as follows.…”
Section: Introductionmentioning
confidence: 99%