Statistical approaches for hidden variables in ecology

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Title:

Author:

Peyrard, Nathalie, editor.

ISBN:

9781119902799

9781119902782

9781119902775

Physical Description:

1 online resource.

Series:

Sciences. Statistics. Statistics and ecology

General Note:

Includes index.

Contents:

Front Matter -- Trajectory Reconstruction and Behavior Identification Using Geolocation Data / Marie-Pierre Etienne, Pierre Gloaguen -- Detection of Eco-Evolutionary Processes in the Wild: Evolutionary Trade-Offs Between Life History Traits / Valentin Journé, Sarah Cubaynes, Julien Papaïx, Mathieu Buoro -- Studying Species Demography and Distribution in Natural Conditions: Hidden Markov Models / Olivier Gimenez, Julie Louvrier, Valentin Lauret, Nina Santostasi -- Inferring Mechanistic Models in Spatial Ecology Using a Mechanistic-Statistical Approach / Julien Papaïx, Samuel Soubeyrand, Olivier Bonnefon, Emily Walker, Julie Louvrier, Etienne Klein, Lionel Roques -- Using Coupled Hidden Markov Chains to Estimate Colonization and Seed Bank Survival in a Metapopulation of Annual Plants / Pierre-Olivier Cheptou, Stéphane Cordeau, Sebastian Le Coz, Nathalie Peyrard -- Using Latent Block Models to Detect Structure in Ecological Networks / Julie Aubert, Pierre Barbillon, Sophie Donnet, Vincent Miele -- Latent Factor Models: A Tool for Dimension Reduction in Joint Species Distribution Models / Daria Bystrova, Giovanni Poggiato, Julyan Arbel, Wilfried Thuiller -- The Poisson Log-Normal Model: A Generic Framework for Analyzing Joint Abundance Distributions / Julien Chiquet, Marie-Josée Cros, Mahendra Mariadassou, Nathalie Peyrard, Stéphane Robin -- Supervised Component-Based Generalized Linear Regression: Method and Extensions / Frédéric Mortier, Jocelyn Chauvet, Catherine Trottier, Guillaume Cornu, Xavier Bry -- Structural Equation Models for the Study of Ecosystems and Socio-Ecosystems / Fabien Laroche, Jérémy Froidevaux, Laurent, Larrieu, Michel Goulard.

Abstract:

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.

Local Note:

John Wiley and Sons

Subject Term:

Ecology -- Statistical methods.

Latent variables.

Variables latentes.

Statistics.

Probability & Statistics.