Chaos in Real Data studies the range of data analytic techniques available to study nonlinear population dynamics for ecological time series. Several case studies are studied using typically short and noisy population data from field and laboratory. A range of modern approaches, such as response surface methodology and mechanistic mathematical modelling, are applied to several case studies. Experts honestly appraise how well these methods have performed on their data. The accessible style of the book ensures its readability for non-quantitative biologists. The data remain available, as benchmarks for future study, on the worldwide web.
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Chaos in Real Data studies the range of data analytic techniques available to study nonlinear population dynamics for ecological time series. Several case studies are studied using typically short and noisy population data from field and laboratory. A range of modern approaches, such as response surface methodology and mechanistic mathematical modelling, are applied to several case studies. Experts honestly appraise how well these methods have performed on their data. The accessible style of the book ensures its readability for non-quantitative biologists. The data remain available, as benchmarks for future study, on the worldwide web.
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Chaos in Real Data studies the range of data analytic techniques available to study nonlinear population dynamics for ecological time series. Several case studies are studied using typically short and noisy population data from field and laborat. Nº de ref. del artículo: 5832411
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Chaos in Real Data studies the range of data analytic techniques available to study nonlinear population dynamics for ecological time series. Several case studies are studied using typically short and noisy population data from field and laboratory. A range of modern approaches, such as response surface methodology and mechanistic mathematical modelling, are applied to several case studies. Experts honestly appraise how well these methods have performed on their data. The accessible style of the book ensures its readability for non-quantitative biologists. The data remain available, as benchmarks for future study, on the worldwide web. 244 pp. Englisch. Nº de ref. del artículo: 9789401057721
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Chaos in Real Data studies the range of data analytic techniques available to study nonlinear population dynamics for ecological time series. Several case studies are studied using typically short and noisy population data from field and laboratory. A range of modern approaches, such as response surface methodology and mechanistic mathematical modelling, are applied to several case studies. Experts honestly appraise how well these methods have performed on their data. The accessible style of the book ensures its readability for non-quantitative biologists. The data remain available, as benchmarks for future study, on the worldwide web. Nº de ref. del artículo: 9789401057721
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Chaos in Real Data studies the range of data analytic techniques available to study nonlinear population dynamics for ecological time series. Several case studies are studied using typically short and noisy population data from field and laboratory. A range of modern approaches, such as response surface methodology and mechanistic mathematical modelling, are applied to several case studies. Experts honestly appraise how well these methods have performed on their data. The accessible style of the book ensures its readability for non-quantitative biologists. The data remain available, as benchmarks for future study, on the worldwide web.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 244 pp. Englisch. Nº de ref. del artículo: 9789401057721
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