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Editorial Reviews
Review
'The book is up-to-date and very comprehensive, yet carefully written, with excellent index and bibliography. Notable features are the worked examples using real data and the profusion of computer-generated plots and diagrams. Undoubtedly, this will become the standard reference work on the application of statistical methods to spherical data.' R. M. Clark, The Australian Journal of Statistics
Product Description
The analysis of data in the form of directions in space, or equivalently of positions or points on a spherical surface, is required in many contexts in the earth sciences, astrophysics and other fields. While the contexts vary, the statistical methodology required is common to most situations, and has been developing rapidly over the last three decades, so that a large body of results and techniques is now disseminated throughout the literature. This book aims to present a unified and up-to-date account of these methods for practical use. The emphasis is on applications with the statistical methods being illustrated throughout the book by data examples from many of the relevant fields. Particular care has been paid to the computational and computer aspects of the procedures, so that there is no gap between the presentation of a technique and its implementation.
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Inside This Book
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First Sentence:
Many different ways of representing a three-dimensional unit vector or axis have been developed over the centuries, due not only to the requirements of disciplines (Astronomy, Geodesy, Geology, Geophysics, Mathematics,...) but also to diverse needs within a discipline: in Geology, for example, there appear to be five or six systems in current use. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
elliptical confidence cone, colatitude plot, sample principal axis, main data mass, common mean direction, plunge azimuth, common principal axis, sample mean direction, unknown mean direction, girdle distribution, girdle model, normalised eigenvalues, spherical random variable, uniform probability plot, mean resultant length, median direction, spherical data, axial data, vectorial data, girdle case, suitable model for the data, sunflower plots, confidence cones, rotationally symmetric distribution, unimodal data Key Phrases - Capitalized Phrases (CAPs): (learn more)
Continuing Example, Right Ascension, Calculate the Kolmogorov-Smirnov, Introduction There New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Many different ways of representing a three-dimensional unit vector or axis have been developed over the centuries, due not only to the requirements of disciplines (Astronomy, Geodesy, Geology, Geophysics, Mathematics,...) but also to diverse needs within a discipline: in Geology, for example, there appear to be five or six systems in current use. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
elliptical confidence cone, colatitude plot, sample principal axis, main data mass, common mean direction, plunge azimuth, common principal axis, sample mean direction, unknown mean direction, girdle distribution, girdle model, normalised eigenvalues, spherical random variable, uniform probability plot, mean resultant length, median direction, spherical data, axial data, vectorial data, girdle case, suitable model for the data, sunflower plots, confidence cones, rotationally symmetric distribution, unimodal data Key Phrases - Capitalized Phrases (CAPs): (learn more)
Continuing Example, Right Ascension, Calculate the Kolmogorov-Smirnov, Introduction There New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 20
books:
See all 20 books this book cites
26
books
cite this book:
See all 26 books citing this book
- Directional Statistics by Kanti V. Mardia in Front Matter, and Back Matter
- Sampling Techniques, 3rd Edition by William G. Cochran in Back Matter
- Spherical Astronomy by Robin M. Green in Back Matter
- Mineralogy: Concepts, Descriptions, Determinations by L. G. Berry in Back Matter
- Paleocurrents and Basin Analysis by Paul Edwin Potter in Back Matter
See all 20 books this book cites
- Computational Geosciences with Mathematica by William C. Haneberg on page 55, and page 171
- Categorical and Directional Data, Volume 2, Spatial Data Analysis by Example by Graham J. G. Upton on page 10, and Back Matter
- Directional Statistics by Kanti V. Mardia in Front Matter, and Back Matter
- Introduction to Color Imaging Science by Hsien-Che Lee in Back Matter
- Multivariate Analysis: Part 2: Classification, Covariance Structures and Repeated Measurements (Pt. 2) by W. J. Krzanowski in Back Matter
See all 26 books citing this book
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