Bayesian data analysis in ecology using linear models with R, BUGS, and Stan /

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their da...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Korner-Nievergelt, Fr�anzi (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam ; Boston : Academic Press, an imprint of Elsevier, [2015]
Temas:
BUGS (Information storage and retrieval system)
Ecology > Research > Statistical methods.
Bayesian statistical decision theory.
R (Computer program language)
Linear models (Statistics)
Bayes Theorem
Linear Models
�Ecologie > Recherche > M�ethodes statistiques.
Th�eorie de la d�ecision bay�esienne.
R (Langage de programmation)
Th�eor�eme de Bayes.
Mod�eles lin�eaires (Statistique)
NATURE > Ecology.
NATURE > Ecosystems & Habitats > Wilderness.
SCIENCE > Environmental Science.
SCIENCE > Life Sciences > Ecology.
Bayesian statistical decision theory
�Okologie
Datenverarbeitung
Bayes-Verfahren
Biostatistik
R > Programm
Gibbs-sampling
ecologie
ecology
gegevensanalyse
data analysis
bayesiaanse theorie
bayesian theory
modellen
models
computer software
Statistical Analysis
Ecology (General)
Statistische analyse
Ecologie (algemeen)
Acceso en línea:Texto completo
Descripción
Sumario:Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, model checking, and multi-model inference, the book also uses effect plots that allow a natural interpretation of data. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN introduces Bayesian software, using R for the simple modes, and flexible Bayesian software (BUGS and Stan) for the more complicated ones. Guiding the ready from easy toward more complex (real) data analyses ina step-by-step manner, the book presents problems and solutions-including all R codes-that are most often applicable to other data and questions, making it an invaluable resource for analyzing a variety of data types.
Descripción Física:1 online resource : illustrations
Bibliografía:Includes bibliographical references and index.
ISBN:9780128016787
0128016787
0128013702
9780128013700

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