03808cam a22004697i 4500
430350
430350
17741205
AT-ISTA
20201022154758.0
130516s2013 enka b 001 0 eng
2013940576
9780199671137
0199671133
(OCoLC)ocn865566482
DLC
eng
CUD
rda
OCLCO
IAD
IXA
ORU
IPL
IAD
UWW
BTCTA
YDXCP
BDX
DLC
lccopycat
QA276
.P45 2013
519.5
23
Pewsey, Arthur,
author.
215240
Circular statistics in R /
Arthur Pewsey, University of Extremadura, Markus Neuhaeuser, RheinAhrCampus, Graeme D. Ruxton, University of St. Andrews.
First edition.
Oxford ;
New York :
Oxford University Press,
2013.
xiv, 183 pages :
illustrations ;
24 cm
text
txt
rdacontent
unmediated
n
rdamedia
volume
nc
rdacarrier
Includes bibliographical references (pages 173-178) 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.
"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. 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. Also provided are over 150 new functions for techniques not already covered in R."--Back cover.
Circular data.
215241
Mathematical statistics.
1277
R (Computer program language)
215242
Neuhaeuser, Markus,
author.
215243
Ruxton, Graeme D.,
author.
202107
Publisher description
http://www.loc.gov/catdir/enhancements/fy1410/2013940576-d.html
Table of contents only
http://www.loc.gov/catdir/enhancements/fy1410/2013940576-t.html
Contributor biographical information
http://www.loc.gov/catdir/enhancements/fy1410/2013940576-b.html
7
cbc
copycat
2
ncip
20
y-gencatlg
ddc
0
0
ddc
0
0
LIB
LIB
2020-10-22
3
32.22
519
AT-ISTA#002168
2020-10-22
32.22
2020-10-22
BOOK