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4.9.1 Deterministic vs. stochastic models
The argument in favour of stochastic models is that if the influence of several unknown factors is sizable, then the exact prediction is not possible, however it is more likely to predict within a known confidence interval.
The stochastic model can be used for time-series where many 104
Contrary to a stochastic model which assumes random walk, a deterministic model assumes that the model variables are fixed.
Therefore the outcome of the model is certain, that consequently leads to the main difference between these two models: in a stochastic model some parameters or elements of the model are sampled from a probability distribution (Startz, 2009).
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