Читать книгу Statistical Approaches for Hidden Variables in Ecology - Nathalie Peyrard - Страница 14

This book provides an overview of recent work on statistical modeling and estimation in latent variable models for ecology. The different chapters illustrate the main principles described above. In some cases, they present statistical methods based on classical models and algorithms; in others, the focus is on developments from recent research in others. Each chapter addresses a specific ecological issue and a modeling approach to solving the problem, illustrated using one or more case studies.

Readers may also access the R code¹ in order to make use of the tools presented here, applied to their own data.

Most of the questions associated with the case studies presented here relate to the comprehension or description of systems. While the issue of forecasting and prediction is touched upon in some chapters, this subject lies outside the main scope of our work. The issue of missing data (i.e. values not observed in samples) is also not addressed either. Finally, note that this work is not an exhaustive summary of latent variable models, or of the inference methods and algorithms used with these models. Each chapter touches on the question of inference in relation to the selected model; readers wishing to explore the subject in greater depth may wish to consult the references provided.

This book is not designed to be read from front to back, but rather as a resource on which ecologists working with models or statisticians working in the field of ecology may draw. Chapters are arranged in order of ecological scale, from individuals up to ecosystems, providing an initial interpretive framework. Another approach would be to consider the nature of the hidden variable being modeled. One final approach would be to examine different statistical models: some models are used in several chapters, in connection with questions on different scales, and using different estimation methods.

Table I.1 gives a summary of the contents of the different chapters and is designed to help readers identify material which is of interest to them.