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![]( "Buchcover ISBN 9781119991960")
„The book is well written and I strongly recommend the book to the users. I have no doubt that many applied statisticians will benefit by the wide coverage of topics in the book.“ (Journal of Time Series Analysis, 9 May 2011)
Statistical Methods for Trend Detection and Analysis in the Environmental Sciences
von Richard Chandler und Marian ScottThe 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.
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.
