Nathalie Peyrard - Statistical Approaches for Hidden Variables in Ecology

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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.<br /><br />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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9 Chapter 9Figure 9.1. Polar representation of VPI (equation 9.3) by values of ℓ for four c...Figure 9.2. Geometric mean of the square mean quadratic prediction errors over r...Figure 9.3. Circles of correlations resulting from the first three components. F...Figure 9.4. Spatial representation of the first three components. For a color ve...Figure 9.5. Geometric mean of the square roots of the mean quadratic prediction ...Figure 9.6. Geometric mean of the RMSE as a function of the number of components...Figure 9.7. Factorial planes (1,2), (1,3) and (2,3) obtained using mixed-SCGLR o...Figure 9.8. Observed and predicted abundance maps for the species with the highe...

10 Chapter 10Figure 10.1. Conventions used in representing an SEM. Latent variables are shown...Figure 10.2. SEM defined a priori for our case study. The exogenous latent varia...Figure 10.3. Main steps in SEM analysis. The diagrams follow the SEM presentatio...Figure 10.4. Estimators of the parameters of the SEM in Figure 10.2. Section A: ...Figure 10.5. SEM resulting from correction of the model shown in Figure 10.2, af...Figure 10.6. Divergences between the correlation matrices of the latent variable...Figure 10.7. SEM resulting from correction of the model in Figure 10.5, limiting...Figure 10.8. Estimated relationships within the relational model of the SEM from...Figure 10.9. Test of causal relations in the relational model shown in Figure 10...

Guide

1 Cover

2 Table of Contents

3 Title Page SCIENCES Statistics, Field Directors – Nikolaos Limnios, Kerrie Mengersen Statistics and Ecology , Subject Head – Nathalie Peyrard

4 Copyright First published 2022 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc. Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address: ISTE Ltd 27-37 St George’s Road London SW19 4EU UK www.iste.co.uk John Wiley & Sons, Inc. 111 River Street Hoboken, NJ 07030 USA www.wiley.com © ISTE Ltd 2022 The rights of Nathalie Peyrard and Olivier Gimenez to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s), contributor(s) or editor(s) and do not necessarily reflect the views of ISTE Group. Library of Congress Control Number: 2021949076 British Library Cataloguing-in-Publication Data A CIP record for this book is available from the British Library ISBN 978-1-78945-047-7 ERC code: PE1 Mathematics PE1_14 Statistics LS8 Ecology, Evolution and Environmental Biology

5 Introduction

6 Begin Reading

7 List of Authors

8 Index

9 End User License Agreement

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SCIENCES

Statistics, Field Directors – Nikolaos Limnios, Kerrie Mengersen

Statistics and Ecology , Subject Head – Nathalie Peyrard

Statistical Approaches for Hidden Variables in Ecology

Coordinated by

Nathalie Peyrard

Olivier Gimenez

First published 2022 in Great Britain and the United States by ISTE Ltd and - фото 2

First published 2022 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

ISTE Ltd

27-37 St George’s Road

London SW19 4EU

UK

www.iste.co.uk

John Wiley & Sons, Inc.

111 River Street

Hoboken, NJ 07030

USA

www.wiley.com

© ISTE Ltd 2022

The rights of Nathalie Peyrard and Olivier Gimenez to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

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