Bernoulli distribution


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Related to Bernoulli distribution: binomial distribution, Bernoulli Principle

Ber·noul·li dis·tri·bu·tion

(bĕr-nū'lē),
the probability distribution associated with two mutually exclusive and exhaustive outcomes, for example, death or survival.
Farlex Partner Medical Dictionary © Farlex 2012

Ber·noul·li dis·tri·bu·tion

(ber-nū'lē dis'tri-byū'shŭn)
Probability distribution that describes likelihood of various combinations of two alternate outcomes in a series of independent trials.
Synonym(s): binomial distribution.
[Jakob Bernoulli, 1654-1705, Swiss mathematician]
Medical Dictionary for the Health Professions and Nursing © Farlex 2012
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Table 1: Average false positive counts on stationary Bernoulli distribution. 0.05 0.1 0.3 0.5 DDM 1.89 0.76 0.29 0.19 EDDM 35.56 36.3 14.42 9.38 ECDD 166.34 157.3 154.01 0.11 DBDM 3.39 0.95 0.05 0.03 Table 2: Average false positive counts on sudden concept drift.
[[xi].sub.i](k) obeys the Bernoulli distribution, so that E[[[xi].sup.i](k)] = [[alpha].sup.i] and E[[([[xi].sup.i]).sup.2](k)] = [[alpha].sup.i], i, j = 1, 2, ..., L.
Only in the scenario in which the assumption of having continuous main features (required by the approaches proposed by us) is not met at all (i.e., for the Bernoulli distribution) do almost all correction approaches perform better than not correcting.
Even if they are similar in size and equally probable, they will follow a Bernoulli distribution, which does not guarantee equal numbers and a uniform distribution.
Let [pi] be the Bernoulli distribution on [S.sup.Z] defined by [pi]([s.sub.i]) [??] [p.sub.i] for all i, and let [mu] be the additive quantity defined by [mu]([s.sub.i]) [??] - log [p.sub.i].
Raghavan and Upfal [1999] considered the model in which n users generate messages according to a Bernoulli distribution with total generation rate up to about 1/10.
This distribution looks very different from the Bernoulli distribution shown in Figure 1a, which has the same mean.
The cell survival is sampled from a Bernoulli distribution where the probability for a given cell to survive is described by the LQ model:
The packet dropouts would be described as a binary sequence which is subject to a Bernoulli distribution taking the value of one or zero with certain probability.
Bernoulli distribution with parameter p [member of] (0, 1), Bern(p).