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In contract to our deterministic model, a stochastic MC model based on the classical reaction diffusion master equation is proposed in [35] based on the ligand-receptor mechanism.
Due to the uncertainty in the description of the occurring diagenesis phases and their effects in the facies deposition model, a stochastic framework may be preferred.
Due to the high complexity of this model a stochastic approach is needed [37].
State space model is a stochastic model which consists of two sub-models: The stochastic system model which is the stochastic model of the system and the observation model which is a statistical model based on available observed data from the system.
We propose two correlated link weight models, namely a deterministic correlated model and a stochastic correlated model.
Our purpose was based on analyzing this behavior using both a deterministic model and a stochastic model.
The mathematical model is a stochastic model a la Gillespie where the cell infection is decomposed into a set of individual steps (binding, uncoating, translation, replication complex formation, circularization, replication, packaging, strand dispersal).
The resulting model can be decomposed into an input-output model and a stochastic innovations model.
Spread of BVDV through the herd was modeled with a stochastic SIR model.
Count uses phylogenetic birth-and-death models in a stochastic probability inference.
Markov models represent a stochastic process used in the economic evaluation of health and disease [ 5].
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