Titre :	Biometry for Forestry and Environmental Data : With Examples in R
Type de document :	texte imprimé
Auteurs :	Juha Lappi, Auteur
Editeur :	London : CRC press
Année de publication :	2022
Importance :	1 vol. (411p.)
Présentation :	ill.en coul.
Format :	25 cm
ISBN/ISSN/EAN :	978-0-367-50845-6
Langues :	Anglais
Catégories :	Ecologie et Environnement - Météorologie - Clémat - Biodiversité Plantes (Botanique)
Mots-clés :	Plantes  écologie
Index. décimale :	577.3 Écologie des forêts
Résumé :	Biometry for Forestry and Environmental Data with Examples in R focuses on statistical methods that are widely applicable in forestry and environmental sciences, but it also includes material that is of wider interest. Features: * Describes the theory and applications of selected statistical methods and illustrates their use and basic concepts through examples with forestry and environmental data in R. * Rigorous but easily accessible presentation of the linear, nonlinear, generalized linear and multivariate models, and their mixed-effects counterparts. Chapters on tree size, tree taper, measurement errors, and forest experiments are also included. * Necessary statistical theory about random variables, estimation and prediction is included. The wide applicability of the linear prediction theory is emphasized. * The hands-on examples with implementations using R make it easier for non-statisticians to understand the concepts and apply the methods with their own data. Lot of additional material is available at www.biombook.org. The book is aimed at students and researchers in forestry and environmental studies, but it will also be of interest to statisticians and researchers in other fields as well.
Note de contenu :	Sommaire: -1- Introduction -2- Random Variables -3- Statistical Modeling, Estimation and Prediction -4- Linear Model -5- Linear Mixed-effects Models -6- More about Linear Mixed-effâ–¡ects Models -7- Nonlinear (Mixed-effâ–¡ects) Models -8- Generalized Linear (Mixed-Eâ–¡ffects) Models -9- Multivariate (Mixed-Effâ–¡ects) Models -10 Additional topics on regression -11 Modeling Tree Size -12 Taper Curves -13 Measurement Errors -14 Forest and Environmental Experiments

Biometry for Forestry and Environmental Data : With Examples in R [texte imprimé] / Juha Lappi, Auteur . - London : CRC press, 2022 . - 1 vol. (411p.) : ill.en coul. ; 25 cm.
ISBN : 978-0-367-50845-6
Langues : Anglais

Catégories :	Ecologie et Environnement - Météorologie - Clémat - Biodiversité Plantes (Botanique)
Mots-clés :	Plantes  écologie
Index. décimale :	577.3 Écologie des forêts
Résumé :	Biometry for Forestry and Environmental Data with Examples in R focuses on statistical methods that are widely applicable in forestry and environmental sciences, but it also includes material that is of wider interest. Features: * Describes the theory and applications of selected statistical methods and illustrates their use and basic concepts through examples with forestry and environmental data in R. * Rigorous but easily accessible presentation of the linear, nonlinear, generalized linear and multivariate models, and their mixed-effects counterparts. Chapters on tree size, tree taper, measurement errors, and forest experiments are also included. * Necessary statistical theory about random variables, estimation and prediction is included. The wide applicability of the linear prediction theory is emphasized. * The hands-on examples with implementations using R make it easier for non-statisticians to understand the concepts and apply the methods with their own data. Lot of additional material is available at www.biombook.org. The book is aimed at students and researchers in forestry and environmental studies, but it will also be of interest to statisticians and researchers in other fields as well.
Note de contenu :	Sommaire: -1- Introduction -2- Random Variables -3- Statistical Modeling, Estimation and Prediction -4- Linear Model -5- Linear Mixed-effects Models -6- More about Linear Mixed-effâ–¡ects Models -7- Nonlinear (Mixed-effâ–¡ects) Models -8- Generalized Linear (Mixed-Eâ–¡ffects) Models -9- Multivariate (Mixed-Effâ–¡ects) Models -10 Additional topics on regression -11 Modeling Tree Size -12 Taper Curves -13 Measurement Errors -14 Forest and Environmental Experiments