Generalized Bernoulli process with long-range dependence and fractional binomial distribution
Bernoulli process is a finite or infinite sequence of independent binary variables, , = 1, 2, · · ·, whose outcome is either 1 or 0 with probability = 1) = , = 0) = 1 – , for a fixed constant ∈ (0, 1). We will relax the independence condition of Bernoulli variables, and develop a generalized Bernoul...
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Veröffentlicht in: | Dependence modeling 2021-03, Vol.8 (1), p.1-12 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Bernoulli process is a finite or infinite sequence of independent binary variables,
,
= 1, 2, · · ·, whose outcome is either 1 or 0 with probability
= 1) =
,
= 0) = 1 –
, for a fixed constant
∈ (0, 1). We will relax the independence condition of Bernoulli variables, and develop a generalized Bernoulli process that is stationary and has auto-covariance function that obeys power law with exponent 2
– 2,
∈ (0, 1). Generalized Bernoulli process encompasses various forms of binary sequence from an independent binary sequence to a binary sequence that has long-range dependence. Fractional binomial random variable is defined as the sum of
consecutive variables in a generalized Bernoulli process, of particular interest is when its variance is proportional to
, if
∈ (1/2, 1). |
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ISSN: | 2300-2298 2300-2298 |
DOI: | 10.1515/demo-2021-0100 |