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Mixed effects models and extensions in ecology with R

Overview of attention for book
Mixed effects models and extensions in ecology with R
Springer New York

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Limitations of Linear Regression Applied on Ecological Data
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    Chapter 3 Things are not Always Linear; Additive Modelling
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    Chapter 4 Dealing with Heterogeneity
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    Chapter 5 Mixed Effects Modelling for Nested Data
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    Chapter 6 Violation of Independence – Part I
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    Chapter 7 Violation of Independence – Part II
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    Chapter 8 Meet the Exponential Family
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    Chapter 9 GLM and GAM for Count Data
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    Chapter 10 GLM and GAM for Absence–Presence and Proportional Data
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    Chapter 11 Zero-Truncated and Zero-Inflated Models for Count Data
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    Chapter 12 Generalised Estimation Equations
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    Chapter 13 GLMM and GAMM
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    Chapter 14 Estimating Trends for Antarctic Birds in Relation to Climate Change
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    Chapter 15 Large-Scale Impacts of Land-Use Change in a Scottish Farming Catchment
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    Chapter 16 Negative Binomial GAM and GAMM to Analyse Amphibian Roadkills
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    Chapter 17 Additive Mixed Modelling Applied on Deep-Sea Pelagic Bioluminescent Organisms
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    Chapter 18 Additive Mixed Modelling Applied on Phytoplankton Time Series Data
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    Chapter 19 Mixed Effects Modelling Applied on American Foulbrood Affecting Honey Bees Larvae
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    Chapter 20 Three-Way Nested Data for Age Determination Techniques Applied to Cetaceans
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    Chapter 21 GLMM Applied on the Spatial Distribution of Koalas in a Fragmented Landscape
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    Chapter 22 A Comparison of GLM, GEE, and GLMM Applied to Badger Activity Data
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    Chapter 23 Incorporating Temporal Correlation in Seal Abundance Data with MCMC
Attention for Chapter 21: GLMM Applied on the Spatial Distribution of Koalas in a Fragmented Landscape
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