Chandler / Scott Statistical Methods for Trend Detection and Analysis in the Environmental Sciences

1. Auflage 2011
ISBN: 978-1-119-99196-0
Verlag: John Wiley & Sons
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 388 Seiten, E-Book

The need to understand and quantify change is fundamentalthroughout the environmental sciences. This might involvedescribing past variation, understanding the mechanisms underlyingobserved changes, making projections of possible future change, ormonitoring the effect of intervening in some environmental system.This book provides an overview of modern statistical techniquesthat may be relevant in problems of this nature.
Practitioners studying environmental change will be familiarwith many classical statistical procedures for the detection andestimation of trends. However, the ever increasing capacity tocollect and process vast amounts of environmental information hasled to growing awareness that such procedures are limited in theinsights that they can deliver. At the same time, significantdevelopments in statistical methodology have often been widelydispersed in the statistical literature and have therefore receivedlimited exposure in the environmental science community. This bookaims to provide a thorough but accessible review of thesedevelopments. It is split into two parts: the first provides anintroduction to this area and the second part presents a collectionof case studies illustrating the practical application of modernstatistical approaches to the analysis of trends in realstudies.
Key Features:
* Presents a thorough introduction to the practical applicationand methodology of trend analysis in environmental science.
* Explores non-parametric estimation and testing as well asparametric techniques.
* Methods are illustrated using case studies from a variety ofenvironmental application areas.
* Looks at trends in all aspects of a process including mean,percentiles and extremes.
* Supported by an accompanying website featuring datasets and Rcode.
The book is designed to be accessible to readers with some basicstatistical training, but also contains sufficient detail to serveas a reference for practising statisticians. It will therefore beof use to postgraduate students and researchers both in theenvironmental sciences and in statistics.

Autoren/Hrsg.

Chandler, Richard

Scott, Marian

Inhaltsverzeichnis

Preface.
Contributing authors.
Part I METHODOLOGY.
1 Introduction.
1.1 What is a trend?
1.2 Why analyse trends?
1.3 Some simple examples.
1.4 Considerations and Difficulties.
1.5 Scope of the book.
1.6 Further reading.
References.
2 Exploratory analysis.
2.1 Data visualisation.
2.2 Simple smoothing.
2.3 Linear filters.
2.4 Classical test procedures.
2.5 Concluding comments.
References.
3 Parametric modelling - deterministic trends.
3.1 The Linear trend.
3.2 Multiple regression techniques.
3.3 Violations of assumptions.
3.4 Nonlinear trends.
3.5 Generalized linear models.
3.6 Inference with small samples.
References.
4 Nonparametric trend estimation.
4.1 An introduction to nonparametric regression.
4.2 Multiple covariates.
4.3 Other nonparametric estimation techniques.
4.4 Parametric or nonparametric?
References.
5 Stochastic trends.
5.1 Stationary time series models and their properties.
5.2 Trend removal via differencing.
5.3 Long memory models.
5.4 Models for irregularly spaced series.
5.5 State space and structural models.
5.6 Nonlinear models.
References.
6 Other issues.
6.1 Multisite data.
6.2 Multivariate series.
6.3 Point process data.
6.4 Trends in extremes.
6.5 Censored data.
References.
Part II CASE STUDIES.
7 Additive models for sulphur dioxide pollution in Europe(Marco Giannitrapani, Adrian Bowman, E. Marian Scott and RonSmith)
7.1 Introduction.
7.2 Additive models with correlated errors.
7.3 Models for the SO2 data.
7.4 Conclusions.
References.
8 Rainfall trends in southwest Western Australia(Richard E. Chandler, Bryson C. Bates and Stephen P.Charles).
8.1 Motivation.
8.2 The study region.
8.3 Data used in the study.
8.4 Modelling methodology.
8.5 Results.
8.6 Summary and conclusions.
References.
9 Estimation of Common tends for tropical index series(Alain F. Zuur, Elena N. Ieno, Christina Mazziotti, GiuseppeMontanari, Attilio Rinaldi and Carla Rita Ferrari).
9.1 Introduction.
9.2 Data exploration.
9.3 Common trends and additive modelling.
9.4 Dynamic factor analysis to estimate common trends.
9.5 Discussion.
Acknowledgement.
References.
10 A Space-time study on forest health (Thomas Kneiband Ludwig Fahrmeir).
10.1 Forest health: survey and data.
10.2 Regression models for longitudinal data with ordinalresponses.
10.3 Spatiotemporal models.
10.4 Spatiotemporal modelling and analysis of forest healthdata.
Acknowledgements.
References.
Index.