BOOK Modelling Population Dynamics - Model Formulation, Fitting And Assessment Using State-Space Methods by Ken Newman Full [PDF ePUB Audiobook]

Free download and read ebooks online Modelling Population Dynamics - Model Formulation, Fitting And Assessment Using State-Space Methods by Ken Newman, Stephen T. Buckland, Byron Morgan, Ruth King, David L. Borchers, Diana Cole, P. Besbeas, Olivier Gimenez, Len Thomas full book PDF ePUB Audiobook. Download a free ebooks and kindle audiobook Modelling Population Dynamics - Model Formulation, Fitting And Assessment Using State-Space Methods with ISBN id 9781493909766 full page with book summary. Ken Newman book PDF ePUB of Modelling Population Dynamics - Model Formulation, Fitting And Assessment Using State-Space Methods published by Springer in 2014-07-17. Modelling Population Dynamics released with category Medical with total 215 pages.

Modelling Population Dynamics - Model Formulation, Fitting And Assessment Using State-Space Methods
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Modelling Population Dynamics - Model Formulation, Fitting And Assessment Using State-Space Methods by Ken Newman free book pdf

This book gives a unifying framework for estimating the abundance of open populations: populations subject to births, deaths and movement, given imperfect measurements or samples of the populations. The focus is primarily on populations of vertebrates for which dynamics are typically modelled within the framework of an annual cycle, and for which stochastic variability in the demographic processes is usually modest. Discrete-time models are developed in which animals can be assigned to discrete states such as age class, gender, maturity, population (within a metapopulation), or species (for multi-species models). The book goes well beyond estimation of abundance, allowing inference on underlying population processes such as birth or recruitment, survival and movement. This requires the formulation and fitting of population dynamics models. The resulting fitted models yield both estimates of abundance and estimates of parameters characterizing the underlying processes.

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