Ecological models and data in R / Benjamin M. Bolker.
Material type: TextLanguage: English Copyright date: Princeton, N.J. : Princeton University Press , 2008Edition: First EditionDescription: vii, 396 pages : illustrations ; 26 cmISBN:- 9780691125220
- 577.015118
- QH541.15.S72 B65 2008
Item type | Current library | Call number | Copy number | Status | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|---|
Colección general | Biblioteca Yachay Tech | 577.015118 B6899e 2008 (Browse shelf(Opens below)) | Ej. 1 | Available | 005581 | |||
Colección general | Biblioteca Yachay Tech | 577.015118 B6899e 2008 (Browse shelf(Opens below)) | Ej. 2 | Available | 005582 | |||
Colección general | Biblioteca Jardín Botánico | 577.015118 B6899e 2008 (Browse shelf(Opens below)) | Ej. 3 | Available | 005583 |
Browsing Biblioteca Yachay Tech shelves Close shelf browser (Hides shelf browser)
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 / | 577.015118 O916b 2007 A biologist's guide to mathematical modeling in ecology and evolution / |
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.
There are no comments on this title.