Biometry for Forestry and Environmental Data Biometry for Forestry and Environmental Data
Chapman & Hall/CRC Applied Environmental Statistics

Biometry for Forestry and Environmental Data

With Examples in R

    • $92.99
    • $92.99

Publisher Description

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.

GENRE
Science & Nature
RELEASED
2020
May 27
LANGUAGE
EN
English
LENGTH
426
Pages
PUBLISHER
CRC Press
SELLER
Taylor & Francis Group
SIZE
17.4
MB
Regression Regression
2022
Recent Advances in Linear Models and Related Areas Recent Advances in Linear Models and Related Areas
2008
Correlated Data Analysis: Modeling, Analytics, and Applications Correlated Data Analysis: Modeling, Analytics, and Applications
2007
Computer Intensive Statistical Methods Computer Intensive Statistical Methods
2017
Industrial Data Analytics for Diagnosis and Prognosis Industrial Data Analytics for Diagnosis and Prognosis
2021
Regression Analysis and its Application Regression Analysis and its Application
2018
A Bayesian Introduction to Fish Population Analysis A Bayesian Introduction to Fish Population Analysis
2025
Spatio-Temporal Models for Ecologists Spatio-Temporal Models for Ecologists
2024
Spatial Linear Models for Environmental Data Spatial Linear Models for Environmental Data
2024
Sampling Strategies for Natural Resources and the Environment Sampling Strategies for Natural Resources and the Environment
2007
Statistics for Environmental Science and Management Statistics for Environmental Science and Management
2008
Bayesian Applications in Environmental and Ecological Studies with R and Stan Bayesian Applications in Environmental and Ecological Studies with R and Stan
2022