A text that focuses on methods of deriving probability distributions on smooth manifolds popular in applied research
Probability Distributions for Directional Data on Smooth Manifolds is a comprehensive text that reviews real-life scientific problems that encounter non-linear data. The authors―noted experts on the topic―present methods for developing distributions on a circle and show how such methods are generalized for other manifolds. In addition, the book explores new methods unique to other manifolds such as disc and hyperdisc.
Designed to be an accessible resource, the book explores the methods from the beginning for a simple manifold and clearly demonstrates how these unfold and generalize to more complicated manifolds. Rather than treating one distribution at a time, the authors develop the generalizations of the methods of derivations. As the outcomes of these generalizations are reviewed, new distributions are presented. In addition, the book provides several illustrative, real-life examples, which not only attest to the ongoing usefulness of these important distributions but can help visualize other modern-day areas of the applications. This important resource:
Written for students of mathematics and statistics and theoretical researchers, Probability Distributions for Directional Data on Smooth Manifolds, the first of its kind, offers a groundbreaking and authoritative guide to the topic.
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Ashis SenGupta, PhD, is Distinguished Professor in the Department of Statistics at Middle East Technical University, Ankara, Turkey; Adjunct Professor in the Department of Population Health Sciences at Augusta University, Georgia, USA; CSIR Emeritus Scientist, Government of India, and Advisor/Consultant and former Professor (Higher Allowance Grade) and Head, ASU, at Indian Statistical Institute, Kolkata, India.
Kunio Shimizu, PhD, is Project Professor in the Center for Training Professors in Statistics at The Institute of Statistical Mathematics, Tokyo, Japan, and Professor Emeritus at Keio University, Yokohama, Japan.
A text that focuses on methods of deriving probability distributions on smooth manifolds popular in applied research
Probability Distributions for Directional Data on Smooth Manifolds is a comprehensive text that reviews real-life scientific problems that encounter non-linear data. The authors--noted experts on the topic--present methods for developing distributions on a circle and show how such methods are generalized for other manifolds. In addition, the book explores new methods unique to other manifolds such as disc and hyperdisc.
Designed to be an accessible resource, the book explores the methods from the beginning for a simple manifold and clearly demonstrates how these unfold and generalize to more complicated manifolds. Rather than treating one distribution at a time, the authors develop the generalizations of the methods of derivations. As the outcomes of these generalizations are reviewed, new distributions are presented. In addition, the book provides several illustrative, real-life examples, which not only attest to the ongoing usefulness of these important distributions but can help visualize other modern-day areas of the applications. This important resource:
Written for students of mathematics and statistics and theoretical researchers, Probability Distributions for Directional Data on Smooth Manifolds, the first of its kind, offers a groundbreaking and authoritative guide to the topic.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Hardcover. Condición: new. Hardcover. A text that focuses on methods of deriving probability distributions on smooth manifolds popular in applied research Probability Distributions for Directional Data on Smooth Manifolds is a comprehensive text that reviews real-life scientific problems that encounter non-linear data. The authorsnoted experts on the topicpresent methods for developing distributions on a circle and show how such methods are generalized for other manifolds. In addition, the book explores new methods unique to other manifolds such as disc and hyperdisc. Designed to be an accessible resource, the book explores the methods from the beginning for a simple manifold and clearly demonstrates how these unfold and generalize to more complicated manifolds. Rather than treating one distribution at a time, the authors develop the generalizations of the methods of derivations. As the outcomes of these generalizations are reviewed, new distributions are presented. In addition, the book provides several illustrative, real-life examples, which not only attest to the ongoing usefulness of these important distributions but can help visualize other modern-day areas of the applications. This important resource: Offers a compilation of the probability distributions of the various manifolds presentedCovers many emerging distributions and topics which have not been covered in any book to datePresents discussions on axial distributions, distributions on the sphere, hemi-sphere and hyper-sphere, and distributions on the (ring) torus and hyper-torusContains information on distributions on the (vertical) cylinder and hyper-cylinder, distributions on the disc and hyper-disc, isotropy and goodness of fit tests, and mathematical formulae Written for students of mathematics and statistics and theoretical researchers, Probability Distributions for Directional Data on Smooth Manifolds, the first of its kind, offers a groundbreaking and authoritative guide to the topic. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781119414063
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Condición: New. Über den AutorAshis SenGupta, PhD, is Professor in the Applied Statistics Unit at Indian Statistical Institute, Kolkata, India. He received his PhD in Statistics from Ohio State University, USA. Dr. SenGupta is also Adjun. Nº de ref. del artículo: 266012858
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