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Circular Statistics in R /Arthur Pewsey, Markus Neuhäuser, Graeme D. Ruxton.

By: Contributor(s): Material type: TextTextPublication details: Oxford : Oxford University Press, (c)2013.Edition: first editionDescription: 1 online resource (xiv, 183 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780191650765
Subject(s): Genre/Form: LOC classification:
  • QA276 .C573 2013
Online resources: Available additional physical forms:
Contents:
Graphical representation of circular data -- Circular summary statistics -- Distribution theory and models for circular random variables -- Basic inference for a single sample -- Model fitting for a single sample -- Comparing two or more samples of circular data -- Correlation and regression.
Subject: "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, both from angular observations, and from daily or seasonal activity patterns. ... 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.
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Holdings
Item type Current library Collection Call number URL Status Date due Barcode
Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD) Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD) G. Allen Fleece Library ONLINE Non-fiction QA276 (Browse shelf(Opens below)) Link to resource Available ocn857712515

Includes bibliographies and index.

Introduction -- Graphical representation of circular data -- Circular summary statistics -- Distribution theory and models for circular random variables -- Basic inference for a single sample -- Model fitting for a single sample -- Comparing two or more samples of circular data -- Correlation and regression.

"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, both from angular observations, and from daily or seasonal activity patterns. ... 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.

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