1987
DOI: 10.1007/bf01086176
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Branching processes. I

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Cited by 26 publications
(8 citation statements)
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“…The continuity theorem (Theorem 9.1) could serve as the basis for a comprehensive theory of long-time scaling limits of critical CSBP, but such a study is beyond the scope of this paper. A large number of results exist in the classical literature that cover supercritical and subcritical cases; see, for example, [2], [18], [25], [27], [40], and [41]. For relatively recent results on critical cases, we refer the reader to [22], [34], and [35].…”
Section: Existence Of Universal Critical Csbpsmentioning
confidence: 99%
“…The continuity theorem (Theorem 9.1) could serve as the basis for a comprehensive theory of long-time scaling limits of critical CSBP, but such a study is beyond the scope of this paper. A large number of results exist in the classical literature that cover supercritical and subcritical cases; see, for example, [2], [18], [25], [27], [40], and [41]. For relatively recent results on critical cases, we refer the reader to [22], [34], and [35].…”
Section: Existence Of Universal Critical Csbpsmentioning
confidence: 99%
“…Moreover, we will also assume that the Perron root of A, i.e., the maximum positive real eigenvalue of A, is greater than one. Thus we deal with the indecomposable supercritical branching process [39]. Physically, this means that, first, a particle of a given type potentially has descendants, either direct or distant, of any type and, second, the number of particles in the system, on average, progressively increases.…”
Section: Branching Processesmentioning
confidence: 99%
“…Therefore, the mean number of particles in each subsystem increases exponentially. Note that the existence of a positive α is equivalent to the condition that the Perron root of A is greater than one [39,40].…”
Section: Branching Processesmentioning
confidence: 99%
“…A proper numerical method for the solution of this conflict is not available to the authors's best knowledge. Previous extensive research on the branching of processes, see [31,32], involved stochastic process models, the construction of which is not feasible in the cases considered herein. An attempt for solution is, thus, made following the approach in [18].…”
Section: Introductionmentioning
confidence: 98%