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Models induced from critical birth-death process with random initial conditions

机译:随机初始条件从关键出生死亡过程引起的模型

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In this work, we study a linear birth-death process starting from random initial conditions. First, we consider these initial conditions as a random number of particles following different standard probabilistic distributions - Negative-Binomial and its closest Geometric, Poisson or Polya-Aeppli distributions. It is proved analytically and numerically that in these cases the random number of particles alive at any positive time follows the same probability law like the initial condition, but with different parameters depending on time. The random initial conditions cannot change the critical parameter of branching mechanism, but they impact the extinction probability. Finally, the numerical model is extended to an application for studying branching processes with more complex initial conditions. This is demonstrated with a linear birth-death process initialised with Polya urn sampling scheme. The obtained preliminary results for particle distribution show close relation to Polya-Aeppli distribution.
机译:在这项工作中,我们从随机初始条件开始研究线性出生死亡过程。首先,我们将这些初始条件视为不同标准概率分布的随机数的粒子 - 负二项式及其最接近的几何,泊松或多元级分布。在分析上并在数值上证明,在这些情况下,在任何阳性时间内活的颗粒随机数遵循相同的概率法,如初始条件,而是根据时间的不同参数。随机初始条件不能改变分支机制的关键参数,但它们会影响灭绝概率。最后,数值模型扩展到用于研究分支过程的应用,具有更复杂的初始条件。这是用PolyA URN采样方案初始化的线性出生死亡过程来证明。获得的颗粒分布的初步结果显示与PolyA-Aeppli分布密切相关。

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