Modelling population processes with random initial conditions

P. K. Pollett, Anthony H Dooley, J. V. Ross

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Population dynamics are almost inevitably associated with two predominant sources of variation: the first, demographic variability, a consequence of chance in progenitive and deleterious events; the second, initial state uncertainty, a consequence of partial observability and reporting delays and errors. Here we outline a general method for incorporating randominitialconditions in population models where a deterministic model is sufficient to describe the dynamics of the population. Additionally, we show that for a large class of stochastic models the overall variation is the sum of variation due to randominitialconditions and variation due to random dynamics, and thus we are able to quantify the variation not accounted for when random dynamics are ignored. Our results are illustrated with reference to both simulated and real data.
Original languageEnglish
Pages (from-to)142-150
JournalMathematical Biosciences
Volume223
Issue number2
DOIs
Publication statusPublished - 1 Feb 2010

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Population Dynamics
Initial conditions
population dynamics
Modeling
Population
Uncertainty
Population dynamics
Observability
Demography
Stochastic models
demographic statistics
uncertainty
Deterministic Model
Population Model
Stochastic Model
Quantify
Sufficient
Partial
methodology

Cite this

Modelling population processes with random initial conditions. / Pollett, P. K.; Dooley, Anthony H; Ross, J. V.

In: Mathematical Biosciences, Vol. 223, No. 2, 01.02.2010, p. 142-150.

Research output: Contribution to journalArticle

Pollett, P. K. ; Dooley, Anthony H ; Ross, J. V. / Modelling population processes with random initial conditions. In: Mathematical Biosciences. 2010 ; Vol. 223, No. 2. pp. 142-150.
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