# Circular Statistics in R

## Pewsey, Arthur; Neuhäuser, Markus; Ruxton, Graeme D

3,2 valoración promedio
( 5 valoraciones por GoodReads )

Review:

It's amazing how often I'm asked for advice about circular statistics. Even simple questions such as 'what's the mean direction?' or 'are species active at different times of day?' require circular statistics and they are rarely catered for in statistical texts. What Pewsey et al. have produced is a long-awaited guide to both the theory and practice of circular statistics with a focus on R. It's a book I'll be consulting frequently and recommending to students and colleagues alike ( Calvin Dytham, University of York)

From the Publisher:

Circular Statistics in R provides the most comprehensive guide to the analysis of circular data in over a decade. Circular data arise in many scientific contexts whether it be angular directions such as: observed compass directions of departure of radio-collared migratory birds from a release point; bond angles measured in different molecules; wind directions at different times of year at a wind farm; direction of stress-fractures in concrete bridge supports; longitudes of earthquake epicentres or seasonal and daily activity patterns, for example: data on the times of day at which animals are caught in a camera trap, or in 911 calls in New York, or in internet traffic; variation throughout the year in measles incidence, global energy requirements, TV viewing figures or injuries to athletes. The natural way of representing such data graphically is as points located around the circumference of a circle, hence their name. Importantly, circular variables are periodic in nature and the origin, or zero point, such as the beginning of a new year, is defined arbitrarily rather than necessarily emerging naturally from the system.

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

## 1.Circular Statistics in R (Paperback)

Editorial: Oxford University Press, United Kingdom (2014)
ISBN 10: 0199671133 ISBN 13: 9780199671137
Librería
The Book Depository
(London, Reino Unido)
Valoración

Descripción Oxford University Press, United Kingdom, 2014. Paperback. Estado de conservación: New. 232 x 156 mm. Language: English . Brand New Book. Circular Statistics in R provides the most comprehensive guide to the analysis of circular data in over a decade. Circular data arise in many scientific contexts whether it be angular directions such as: observed compass directions of departure of radio-collared migratory birds from a release point; bond angles measured in different molecules; wind directions at different times of year at a wind farm; direction of stress-fractures in concrete bridge supports; longitudes of earthquake epicentres or seasonal and daily activity patterns, for example: data on the times of day at which animals are caught in a camera trap, or in 911 calls in New York, or in internet traffic; variation throughout the year in measles incidence, global energy requirements, TV viewing figures or injuries to athletes. The natural way of representing such data graphically is as points located around the circumference of a circle, hence their name. Importantly, circular variables are periodic in nature and the origin, or zero point, such as the beginning of a new year, is defined arbitrarily rather than necessarily emerging naturally from the system. 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. Nº de ref. de la librería AOP9780199671137

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## 2.Circular Statistics in R (Paperback)

Editorial: Oxford University Press, United Kingdom (2014)
ISBN 10: 0199671133 ISBN 13: 9780199671137
Librería
The Book Depository US
(London, Reino Unido)
Valoración

Descripción Oxford University Press, United Kingdom, 2014. Paperback. Estado de conservación: New. 232 x 156 mm. Language: English . Brand New Book. Circular Statistics in R provides the most comprehensive guide to the analysis of circular data in over a decade. Circular data arise in many scientific contexts whether it be angular directions such as: observed compass directions of departure of radio-collared migratory birds from a release point; bond angles measured in different molecules; wind directions at different times of year at a wind farm; direction of stress-fractures in concrete bridge supports; longitudes of earthquake epicentres or seasonal and daily activity patterns, for example: data on the times of day at which animals are caught in a camera trap, or in 911 calls in New York, or in internet traffic; variation throughout the year in measles incidence, global energy requirements, TV viewing figures or injuries to athletes. The natural way of representing such data graphically is as points located around the circumference of a circle, hence their name. Importantly, circular variables are periodic in nature and the origin, or zero point, such as the beginning of a new year, is defined arbitrarily rather than necessarily emerging naturally from the system. 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. Nº de ref. de la librería AOP9780199671137

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## 3.Circular Statistics in R

Editorial: Oxford University Press 2014-01-01 (2014)
ISBN 10: 0199671133 ISBN 13: 9780199671137
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Descripción Oxford University Press 2014-01-01, 2014. PAPERBACK. Estado de conservación: New. 0199671133 BRAND NEW. Over 1,000,000 satisfied customers since 1997! We ship daily M-F. Choose expedited shipping (if available) for much faster delivery. Delivery confirmation on all US orders. Nº de ref. de la librería Z0199671133ZN

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## 4.Circular Statistics in R

Editorial: Oxford University Press 2013-09-26, Oxford (2013)
ISBN 10: 0199671133 ISBN 13: 9780199671137
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Blackwell's
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Descripción Oxford University Press 2013-09-26, Oxford, 2013. paperback. Estado de conservación: New. Nº de ref. de la librería 9780199671137

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## 5.Circular Statistics in R

Editorial: Oxford University Press
ISBN 10: 0199671133 ISBN 13: 9780199671137
Librería
THE SAINT BOOKSTORE
(Southport, Reino Unido)
Valoración

Descripción Oxford University Press. Paperback. Estado de conservación: new. BRAND NEW, Circular Statistics in R, Arthur Pewsey, Markus Neuhauser, Graeme D. Ruxton, Circular Statistics in R provides the most comprehensive guide to the analysis of circular data in over a decade. Circular data arise in many scientific contexts whether it be angular directions such as: observed compass directions of departure of radio-collared migratory birds from a release point; bond angles measured in different molecules; wind directions at different times of year at a wind farm; direction of stress-fractures in concrete bridge supports; longitudes of earthquake epicentres or seasonal and daily activity patterns, for example: data on the times of day at which animals are caught in a camera trap, or in 911 calls in New York, or in internet traffic; variation throughout the year in measles incidence, global energy requirements, TV viewing figures or injuries to athletes. The natural way of representing such data graphically is as points located around the circumference of a circle, hence their name. Importantly, circular variables are periodic in nature and the origin, or zero point, such as the beginning of a new year, is defined arbitrarily rather than necessarily emerging naturally from the system. 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. Nº de ref. de la librería B9780199671137

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## 6.Circular Statistics in R

Editorial: Oxford University Press, USA
ISBN 10: 0199671133 ISBN 13: 9780199671137
Nuevos Tapa blanda Primera edición Cantidad: 1
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Descripción Oxford University Press, USA. Estado de conservación: New. 2014. 1st Edition. Paperback. Measurements like mass, length and speed are "; 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 explains how to easily and effectively analyse circular data statistically. Num Pages: 208 pages, illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 230 x 158 x 12. Weight in Grams: 328. . . . . . . Nº de ref. de la librería V9780199671137

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## 7.Circular Statistics in R

Editorial: OUP Oxford (2013)
ISBN 10: 0199671133 ISBN 13: 9780199671137
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Descripción OUP Oxford, 2013. PAP. Estado de conservación: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Nº de ref. de la librería FU-9780199671137

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## 8.Circular Statistics in R

Editorial: Oxford University Press, USA
ISBN 10: 0199671133 ISBN 13: 9780199671137
Librería
Kennys Bookstore
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Descripción Oxford University Press, USA. Estado de conservación: New. 2014. 1st Edition. Paperback. Measurements like mass, length and speed are "; 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 explains how to easily and effectively analyse circular data statistically. Num Pages: 208 pages, illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 230 x 158 x 12. Weight in Grams: 328. . . . . . Books ship from the US and Ireland. Nº de ref. de la librería V9780199671137

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## 9.Circular Statistics in R

Editorial: OUP Oxford (2013)
ISBN 10: 0199671133 ISBN 13: 9780199671137
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Ria Christie Collections
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Descripción OUP Oxford, 2013. Estado de conservación: New. book. Nº de ref. de la librería ria9780199671137_rkm

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## 10.Circular Statistics in R

Editorial: OUP Oxford (2013)
ISBN 10: 0199671133 ISBN 13: 9780199671137
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Green Books
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Descripción OUP Oxford, 2013. Paperback. Estado de conservación: New. Brand New Book. Shipping: Once your order has been confirmed and payment received, your order will then be processed. The book will be located by our staff, packaged and despatched to you as quickly as possible. From time to time, items get mislaid en route. If your item fails to arrive, please contact us first. We will endeavour to trace the item for you and where necessary, replace or refund the item. Please do not leave negative feedback without contacting us first. All orders will be dispatched within two working days. If you have any quesions please contact us. Nº de ref. de la librería V9780199671137

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