2008 · 120 citations · 14 references
EngineeringMathematicsDynamical SystemsProbability TheoryStochastic ProcessesBirth-death ProcessesMarkov ChainsMarkov ProcessesNetwork DynamicsStochastic NetworksMarkov Chains On GraphsMarkovian Network ModelsRandom Graph ModelsRandom Graph TheoryRandom GraphsStochastic Birth-death ProcessesStochastic Processes On NetworksTime-dependent Transitions
We introduce stochastic time-dependency in evolving graphs: starting from an arbitrary initial edge probability distribution, at every time step, every edge changes its state (existing or not) according to a two-state Markovian process with probabilities p (edge birth-rate) and q (edge death-rate). If an edge exists at time t then, at time t+1, it dies with probability q. If instead the edge does not exist at time t, then it will come into existence at time t+1 with probability p.
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