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Statistical Approaches for Hidden Variables in Ecology
About this book
The study of ecological systems is often impeded by components that escape perfect observation, such as the trajectories of moving animals or the status of plant seed banks. These hidden components can be efficiently handled with statistical modeling by using hidden variables, which are often called latent variables. Notably, the hidden variables framework enables us to model an underlying interaction structure between variables (including random effects in regression models) and perform data clustering, which are useful tools in the analysis of ecological data.
This book provides an introduction to hidden variables in ecology, through recent works on statistical modeling as well as on estimation in models with latent variables. All models are illustrated with ecological examples involving different types of latent variables at different scales of organization, from individuals to ecosystems. Readers have access to the data and R codes to facilitate understanding of the model and to adapt inference tools to their own data.
This book provides an introduction to hidden variables in ecology, through recent works on statistical modeling as well as on estimation in models with latent variables. All models are illustrated with ecological examples involving different types of latent variables at different scales of organization, from individuals to ecosystems. Readers have access to the data and R codes to facilitate understanding of the model and to adapt inference tools to their own data.
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Yes, you can access Statistical Approaches for Hidden Variables in Ecology by Nathalie Peyrard,Olivier Gimenez in PDF and/or ePUB format, as well as other popular books in Social Sciences & Probability & Statistics. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Half-Title Page
- Title Page
- Copyright Page
- Contents
- Introduction
- 1. Trajectory Reconstruction and Behavior Identification Using Geolocation Data
- 2. Detection of Eco-Evolutionary Processes in the Wild: Evolutionary Trade-Offs Between Life History Traits
- 3. Studying Species Demography and Distribution in Natural Conditions: Hidden Markov Models
- 4. Inferring Mechanistic Models in Spatial Ecology Using a Mechanistic-Statistical Approach
- 5. Using Coupled Hidden Markov Chains to Estimate Colonization and Seed Bank Survival in a Metapopulation of Annual Plants
- 6. Using Latent Block Models to Detect Structure in Ecological Networks
- 7. Latent Factor Models: A Tool for Dimension Reduction in Joint Species Distribution Models
- 8. The Poisson Log-Normal Model: A Generic Framework for Analyzing Joint Abundance Distributions
- 9. Supervised Component-Based Generalized Linear Regression: Method and Extensions
- 10. Structural Equation Models for the Study of Ecosystems and Socio-Ecosystems
- List of Authors
- Index
- EULA