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A comparison of probabilistic and stochastic formulations in modelling growth uncertainty and variability
H T Banks1, J L Davis, S L Ernstberger
1Center for Research in Scientific Computation, North Carolina State University, Raleigh, NC, USA. htbanks@ncsu.edu
Abstract:
We compare two approaches for inclusion of uncertainty/variability in modelling growth in size-structured population models. One entails imposing a probabilistic structure on growth rates in the population while the other involves formulating growth as a stochastic Markov diffusion process. We present a theoretical analysis that allows one to include comparable levels of uncertainty in the two distinct formulations in making comparisons of the two approaches.
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