Ecological models and data in R / Benjamin M. Bolker.
Tipo de material: TextoIdioma: Inglés Fecha de copyright: Princeton, N.J. : Princeton University Press , 2008Edición: First EditionDescripción: vii, 396 pages : illustrations ; 26 cmISBN:- 9780691125220
- 577.015118 23
- QH541.15.S72 B65 2008
Tipo de ítem | Biblioteca actual | Signatura | Copia número | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems | |
---|---|---|---|---|---|---|---|---|
Colección general | Biblioteca Yachay Tech | 577.015118 B6899e 2008 (Navegar estantería(Abre debajo)) | Ej. 1 | Disponible | 005581 | |||
Colección general | Biblioteca Yachay Tech | 577.015118 B6899e 2008 (Navegar estantería(Abre debajo)) | Ej. 2 | Disponible | 005582 | |||
Colección general | Biblioteca Jardín Botánico | 577.015118 B6899e 2008 (Navegar estantería(Abre debajo)) | Ej. 3 | Disponible | 005583 |
Navegando Biblioteca Yachay Tech estanterías Cerrar el navegador de estanterías (Oculta el navegador de estanterías)
577 S7287e 1991 Ecological methods : | 577 V246c 1980 Conceptos unificadores en ecología / | 577.01 E1936 2006 Ecological census techniques : | 577.015118 B6899e 2008 Ecological models and data in R / | 577.015118 B6899e 2008 Ecological models and data in R / | 577.015118 B6899e 2008 Ecological models and data in R / | 577.015118 M4672s 1974 Stability and complexity in model ecosystems / |
Includes bibliographical references (page 369-382) and indexes.
Introduction and background -- Exploratory data analysis and graphics -- Deterministic functions for ecological modeling -- Probability and stochastic distributions for ecological modeling -- Stochastic simulation and power analysis -- Likelihood and all that -- Optimization and all that -- Likelihood examples -- Standard statistics revisited -- Modeling variance -- Dynamic models -- Afterword -- Appendix: Algebra and calculus basics.
Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and Bayesian techniques to analyze their own data using the programming language R. Drawing on extensive experience teaching these techniques to graduate students in ecology, Benjamin Bolker shows how to choose among and construct statistical models for data, estimate their parameters and confidence limits, and interpret the results. The book also covers statistical frameworks, the philosophy of statistical modeling, and critical mathematical functions and probability distributions. It requires no programming background - only basic calculus and statistics.
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