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＜電子ブック＞
Modelling Population Dynamics : Model Formulation, Fitting and Assessment using State-Space Methods / by K. B. Newman, S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole, P. Besbeas, O. Gimenez, L. Thomas
(Methods in Statistical Ecology. ISSN:21993203)

版	1st ed. 2014.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	2014
本文言語	英語
大きさ	XII, 215 p. 38 illus., 21 illus. in color : online resource
著者標目	*Newman, K. B author Buckland, S. T author Morgan, B. J. T author King, R author Borchers, D. L author Cole, D. J author Besbeas, P author Gimenez, O author Thomas, L author SpringerLink (Online service)
件　名	LCSH:Biometry FREE:Biostatistics
一般注記	Introduction -- Matrices as Building Blocks -- State-space Models -- Fitting State-space models -- Model Formulation and Evaluation -- Modelling Population Dynamics Using Closed-population Abundance Estimates -- Estimating Survival Probabilities from Mark-re-encounter Data -- Estimating Abundance from Mark-recapture Data -- Integrated Population Modelling -- Concluding Remarks 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.   HTTP:URL=https://doi.org/10.1007/978-1-4939-0977-3

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