Modern Directional Statistics

Author : Christophe Ley,Thomas Verdebout
Publisher : CRC Press
Page : 191 pages
File Size : 47,9 Mb
Release : 2017-08-03
Category : Computers
ISBN : 9781498706667

Get Book

Modern Directional Statistics by Christophe Ley,Thomas Verdebout Pdf

Modern Directional Statistics collects important advances in methodology and theory for directional statistics over the last two decades. It provides a detailed overview and analysis of recent results that can help both researchers and practitioners. Knowledge of multivariate statistics eases the reading but is not mandatory. The field of directional statistics has received a lot of attention over the past two decades, due to new demands from domains such as life sciences or machine learning, to the availability of massive data sets requiring adapted statistical techniques, and to technological advances. This book covers important progresses in distribution theory,high-dimensional statistics, kernel density estimation, efficient inference on directional supports, and computational and graphical methods. Christophe Ley is professor of mathematical statistics at Ghent University. His research interests include semi-parametrically efficient inference, flexible modeling, directional statistics and the study of asymptotic approximations via Stein’s Method. His achievements include the Marie-Jeanne Laurent-Duhamel prize of the Société Française de Statistique and an elected membership at the International Statistical Institute. He is associate editor for the journals Computational Statistics & Data Analysis and Econometrics and Statistics. Thomas Verdebout is professor of mathematical statistics at Université libre de Bruxelles (ULB). His main research interests are semi-parametric statistics, high- dimensional statistics, directional statistics and rank-based procedures. He has won an annual prize of the Belgian Academy of Sciences and is an elected member of the International Statistical Institute. He is associate editor for the journals Statistics and Probability Letters and Journal of Multivariate Analysis.

Author : Christophe Ley,Thomas Verdebout
Publisher : Unknown
Page : 128 pages
File Size : 41,8 Mb
Release : 2019
Category : Circular data
ISBN : 1315228572

Get Book

Applied Directional Statistics by Christophe Ley,Thomas Verdebout Pdf

Author : Christophe Ley,Thomas Verdebout
Publisher : CRC Press
Page : 300 pages
File Size : 54,6 Mb
Release : 2020-12-18
Category : Circular data
ISBN : 0367733455

Get Book

Applied Directional Statistics by Christophe Ley,Thomas Verdebout Pdf

This book collects important advances in methodology and data analysis for directional statistics. It is the companion book of the more theoretical treatment presented in Modern Directional Statistics (CRC Press, 2017). The field of directional statistics has received a lot of attention due to demands from disciplines such as life sciences or machine learning, the availability of massive data sets requiring adapted statistical techniques, and technological advances. This book covers important progress in bioinformatics, biology, astrophysics, oceanography, environmental sciences, earth sciences, machine learning and social sciences.

Author : Kanti V. Mardia,Peter E. Jupp
Publisher : John Wiley & Sons
Page : 472 pages
File Size : 54,8 Mb
Release : 2000
Category : Mathematics
ISBN : UOM:39015053172394

Get Book

Directional Statistics by Kanti V. Mardia,Peter E. Jupp Pdf

Observations which are directions, axes or rotations occur in many sciences, including astronomy, biology, earth sciences, image analysis, and medicine. To analyse such data it is necessary to use the techniques of directional statistics, in which the special structure of circles, spheres and rotation groups is taken into account. This book gives a unified and comprehensive account of directional statistics, presenting both the underlying statistical theory and the practical methodology. The book is divided into three parts. The first part concentrates on statistics on the circle. Topics covered include tests of uniformity, tests of goodness-of-fit, inference on von Mises distributions and non-parametric methods. The second part considers statistics on spheres of arbitrary dimension, and includes a detailed account of inference on the main distributions on spheres. Recent material on correlation, regression, time series, robust techniques, bootstrap methods, density estimation and curve fitting is presented. The third part considers statistics on more general sample spaces, in particular rotation groups, Stiefel manifolds, Grassmann manifolds and complex projective spaces. Shape analysis is considered from the perspective of directional statistics. This text will be invaluable not only to researchers in probability and statistics interested in the latest developments in directional statistics, but also to practitioners and researchers in many scientific fields, including astronomy, biology, computer vision, earth sciences and image analysis.

Author : N. I. Fisher
Publisher : Cambridge University Press
Page : 300 pages
File Size : 42,6 Mb
Release : 1995-10-12
Category : Mathematics
ISBN : 0521568900

Get Book

Statistical Analysis of Circular Data by N. I. Fisher Pdf

A unified, up-to-date account of circular data-handling techniques, useful throughout science.

Author : Christophe Ley,Thomas Verdebout
Publisher : CRC Press
Page : 300 pages
File Size : 55,9 Mb
Release : 2018-09-03
Category : Mathematics
ISBN : 9781351856522

Get Book

Applied Directional Statistics by Christophe Ley,Thomas Verdebout Pdf

This book collects important advances in methodology and data analysis for directional statistics. It is the companion book of the more theoretical treatment presented in Modern Directional Statistics (CRC Press, 2017). The field of directional statistics has received a lot of attention due to demands from disciplines such as life sciences or machine learning, the availability of massive data sets requiring adapted statistical techniques, and technological advances. This book covers important progress in bioinformatics, biology, astrophysics, oceanography, environmental sciences, earth sciences, machine learning and social sciences.

Author : Arthur Pewsey,Markus Neuhäuser,Graeme D Ruxton
Publisher : OUP Oxford
Page : 192 pages
File Size : 50,7 Mb
Release : 2013-09-26
Category : Mathematics
ISBN : 9780191650765

Get Book

Circular Statistics in R by Arthur Pewsey,Markus Neuhäuser,Graeme D Ruxton Pdf

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.

Author : A V Dattatreya Rao,S V S Girija
Publisher : CRC Press
Page : 255 pages
File Size : 41,6 Mb
Release : 2019-12-20
Category : Mathematics
ISBN : 9781000739633

Get Book

Angular Statistics by A V Dattatreya Rao,S V S Girija Pdf

Directional data arise in the form of circular / semicircular / axial, symmetric / asymmetric, uni / bimodal data, in practical situations of varied fields. For the purpose of modeling such kind of data sets, the data scientists found that existing models as inadequate. As there is paucity of angular models, and to fill the gap, this book is designed at constructing new angular models with the existing techniques and to develop new tools of constructing angular models with an application to control charts in angular models. This book is planned to cover the following topics in nine chapters Wrapped, stereographic and offset circular models Construction of angular models using Rising Sun function, positive definite sequences, discretization and through differential approach Extemporaneous Semicircular / arc and asymmetric l – axial models Choice of angular models as an inferential aspect and construction of control charts for angular data as an application are presented. This graduate level book will be useful for data scientists, researchers and research students of Statistics and allied fields.

Author : Ashis SenGupta,Barry C. Arnold
Publisher : Springer Nature
Page : 487 pages
File Size : 43,8 Mb
Release : 2022-06-15
Category : Mathematics
ISBN : 9789811910449

Get Book

Directional Statistics for Innovative Applications by Ashis SenGupta,Barry C. Arnold Pdf

In commemoration of the bicentennial of the birth of the “lady who gave the rose diagram to us”, this special contributed book pays a statistical tribute to Florence Nightingale. This book presents recent phenomenal developments, both in rigorous theory as well as in emerging methods, for applications in directional statistics, in 25 chapters with contributions from 65 renowned researchers from 25 countries. With the advent of modern techniques in statistical paradigms and statistical machine learning, directional statistics has become an indispensable tool. Ranging from data on circles to that on the spheres, tori and cylinders, this book includes solutions to problems on exploratory data analysis, probability distributions on manifolds, maximum entropy, directional regression analysis, spatio-directional time series, optimal inference, simulation, statistical machine learning with big data, and more, with their innovative applications to emerging real-life problems in astro-statistics, bioinformatics, crystallography, optimal transport, statistical process control, and so on.

Author : Larry Wasserman
Publisher : Springer Science & Business Media
Page : 446 pages
File Size : 52,8 Mb
Release : 2013-12-11
Category : Mathematics
ISBN : 9780387217369

Get Book

All of Statistics by Larry Wasserman Pdf

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

Author : Mark Stemmler,Alexander von Eye,Wolfgang Wiedermann
Publisher : Springer
Page : 385 pages
File Size : 49,6 Mb
Release : 2015-10-19
Category : Social Science
ISBN : 9783319205854

Get Book

Dependent Data in Social Sciences Research by Mark Stemmler,Alexander von Eye,Wolfgang Wiedermann Pdf

This volume presents contributions on handling data in which the postulate of independence in the data matrix is violated. When this postulate is violated and when the methods assuming independence are still applied, the estimated parameters are likely to be biased, and statistical decisions are very likely to be incorrect. Problems associated with dependence in data have been known for a long time, and led to the development of tailored methods for the analysis of dependent data in various areas of statistical analysis. These methods include, for example, methods for the analysis of longitudinal data, corrections for dependency, and corrections for degrees of freedom. This volume contains the following five sections: growth curve modeling, directional dependence, dyadic data modeling, item response modeling (IRT), and other methods for the analysis of dependent data (e.g., approaches for modeling cross-section dependence, multidimensional scaling techniques, and mixed models). Researchers and graduate students in the social and behavioral sciences, education, econometrics, and medicine will find this up-to-date overview of modern statistical approaches for dealing with problems related to dependent data particularly useful.

Author : Peter Bruce,Andrew Bruce
Publisher : "O'Reilly Media, Inc."
Page : 395 pages
File Size : 44,5 Mb
Release : 2017-05-10
Category : Computers
ISBN : 9781491952917

Get Book

Practical Statistics for Data Scientists by Peter Bruce,Andrew Bruce Pdf

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

Author : S. Ejaz Ahmed
Publisher : Springer
Page : 386 pages
File Size : 53,8 Mb
Release : 2017-03-21
Category : Mathematics
ISBN : 9783319415734

Get Book

Big and Complex Data Analysis by S. Ejaz Ahmed Pdf

This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Its peer-reviewed contributions showcase recent advances in variable selection, estimation and prediction strategies for a host of useful models, as well as essential new developments in the field. The continued and rapid advancement of modern technology now allows scientists to collect data of increasingly unprecedented size and complexity. Examples include epigenomic data, genomic data, proteomic data, high-resolution image data, high-frequency financial data, functional and longitudinal data, and network data. Simultaneous variable selection and estimation is one of the key statistical problems involved in analyzing such big and complex data. The purpose of this book is to stimulate research and foster interaction between researchers in the area of high-dimensional data analysis. More concretely, its goals are to: 1) highlight and expand the breadth of existing methods in big data and high-dimensional data analysis and their potential for the advancement of both the mathematical and statistical sciences; 2) identify important directions for future research in the theory of regularization methods, in algorithmic development, and in methodologies for different application areas; and 3) facilitate collaboration between theoretical and subject-specific researchers.

Author : Gary L. Gaile,James E. Burt
Publisher : Geo Abstracts Limited
Page : 52 pages
File Size : 53,6 Mb
Release : 1980
Category : Science
ISBN : UCAL:B4980391

Get Book

Directional Statistics by Gary L. Gaile,James E. Burt Pdf

Author : Kanti V. Mardia,Peter E. Jupp
Publisher : John Wiley & Sons
Page : 460 pages
File Size : 49,8 Mb
Release : 2009-09-25
Category : Mathematics
ISBN : 9780470317815

Get Book

Directional Statistics by Kanti V. Mardia,Peter E. Jupp Pdf

Presents new and up-dated material on both the underlying theory and the practical methodology of directional statistics, helping the reader to utilise and develop the techniques appropriate to their work. The book is divided into three parts. The first part concentrates on statistics on the circle. Topics covered include tests of uniformity, tests of good-of-fit, inference on von Mises distributions and non-parametric methods. The second part considers statistics on spheres of arbitrary dimension, and includes a detailed account of inference on the main distributions on spheres. Recent material on correlation, regression time series, robust techniques, bootstrap methods, density estimation and curve fitting is presented. The third part considers statistics on more general sample spaces, in particular rotation groups, Stiefel manifolds, Grassmann manifolds and complex projective spaces. Shape analysis is considered from the perspective of directional statistics. Written by leading authors in the field, this text will be invaluable not only to researchers in probability and statistics interested in the latest developments in directional statistics, but also to practitioners and researchers in many scientific fields, including astronomy, biology, computer vision, earth sciences and image analysis.