Circular Statistics in R
Language: English
Published by KNV Besorgung|Oxford University Press, 2014
- Softcover
- New
Condition: New
£ 65.78
Quantity: Over 20 available
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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Measurements like mass, length and speed are linear but compass direction or the time of the year are circular . Circular data have a repeating nature and an arbitrary zero: 12 months after the 1st of July it is the 1st of July again. This book explai.
Seller Inventory # 594431410
- Title
- Circular Statistics in R
- Author
- Pewsey, Arthur|Neuhäuser, Markus|Ruxton, Graeme D.
- Publisher
- KNV Besorgung|Oxford University Press
- Publication year
- 2014
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 0199671133
- ISBN 13
- 9780199671137
This book will be of value both to those new to circular data analysis as well as those more familiar with the field. For beginners, the authors start by considering the fundamental graphical and numerical summaries used to represent circular data before introducing distributions that might be used to model them. They go on to discuss basic forms of inference such as point and interval estimation, as well as formal significance tests for hypotheses that will often be of scientific interest. When discussing model fitting, the authors advocate reduced reliance on the classical von Mises distribution; showcasing distributions that are capable of modelling features such as asymmetry and varying levels of kurtosis that are often exhibited by circular data.
The use of likelihood-based and computer-intensive approaches to inference and modelling are stressed throughout the book. The R programming language is used to implement the methodology, particularly its "circular" package. Also provided are over 150 new functions for techniques not already covered within R.
This concise but authoritative guide is accessible to the diverse range of scientists who have circular data to analyse and want to do so as easily and as effectively as possible.
"Synopsis" may belong to another edition of this title.
About the Author
Markus Neuhäuser is Professor of Statistics at the RheinAhrCampus Remagen, Germany. He is an expert in computer-intensive statistical methods. Markus is Associate Editor of Journal of Statistical Computation and Simulation , Communications in Statistics: Theory and Methods and Communications in Statistics: Simulation and Computation
Graeme D Ruxton is Professor of Ecology at the University of St Andrews. He is a biologist with particular interest in making modern statistical techniques accessible to broad user groups.
"About the title" may belong to another edition of this title.
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