Advances in Directional and Linear Statistics PDF Download

Author: Martin T. Wells
Publisher: Springer Science & Business Media
ISBN: 3790826286
Category : Mathematics
Languages : en
Pages : 326

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Book Description
The present volume consists of papers written by students, colleagues and collaborators of Sreenivasa Rao Jammalamadaka from various countries, and covers a variety of research topics which he enjoys and contributed immensely to.

Author:
Publisher:
ISBN: 9781282996724
Category :
Languages : en
Pages :

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Book Description

Author: Martin T Wells
Publisher: Springer
ISBN: 9783790826296
Category :
Languages : en
Pages : 336

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Book Description

Author: Martin T. Wells
Publisher: Physica
ISBN: 9783790826272
Category : Mathematics
Languages : en
Pages : 321

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Book Description
The present volume consists of papers written by students, colleagues and collaborators of Sreenivasa Rao Jammalamadaka from various countries, and covers a variety of research topics which he enjoys and contributed immensely to.

Author: Christophe Ley
Publisher: CRC Press
ISBN: 1351856529
Category : Mathematics
Languages : en
Pages : 400

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Book Description
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: Christophe Ley
Publisher: CRC Press
ISBN: 1498706665
Category : Computers
Languages : en
Pages : 191

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Book Description
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: Ashis SenGupta
Publisher: Springer Nature
ISBN: 9811910448
Category : Mathematics
Languages : en
Pages : 487

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Book Description
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: Arnab Kumar Laha
Publisher: Springer
ISBN: 9811312087
Category : Business & Economics
Languages : en
Pages : 289

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Book Description
This book includes selected papers submitted to the ICADABAI-2017 conference, offering an overview of the new methodologies and presenting innovative applications that are of interest to both academicians and practitioners working in the area of analytics. It discusses predictive analytics applications, machine learning applications, human resource analytics, operations analytics, analytics in finance, methodology and econometric applications. The papers in the predictive analytics applications section discuss web analytics, email marketing, customer churn prediction, retail analytics and sports analytics. The section on machine learning applications then examines healthcare analytics, insurance analytics and machine analytics using different innovative machine learning techniques. Human resource analytics addresses important issues relating to talent acquisition and employability using analytics, while a paper in the section on operations analytics describe an innovative application in oil and gas industry. The papers in the analytics in finance part discuss the use of analytical tools in banking and commodity markets, and lastly the econometric applications part presents interesting banking and insurance applications.

Author: Elena Popkova
Publisher: World Scientific
ISBN: 9811279209
Category : Business & Economics
Languages : en
Pages : 299

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Book Description
This book explains complex scientific concepts using simple and understandable illustrations and practical examples. For example, the competition between countries in the world economy is compared to motor racing, time savings are illustrated through the example of a masquerade ball, and the cyclical effect of time on the economy is reflected through the prism of changing seasons. It presents amazing phenomena and processes of economic time, including 'economic vintage', 'the time machine in the economy', 'youth' and 'old age' of the economy, its 'growing up', 'the economic calendar', 'catching up', and 'forward-looking' development. This book will therefore be interesting not only to members of the scientific community but also to non-academic readers — to everyone who wants to understand the nature of economic time.

Author: Ricardo Cao
Publisher: Springer
ISBN: 3319415824
Category : Mathematics
Languages : en
Pages : 231

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Book Description
This volume collects selected, peer-reviewed contributions from the 2nd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Cádiz (Spain) between June 11–16 2014, and sponsored by the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and Universidad Carlos III de Madrid. The 15 articles are a representative sample of the 336 contributed papers presented at the conference. They cover topics such as high-dimensional data modelling, inference for stochastic processes and for dependent data, nonparametric and goodness-of-fit testing, nonparametric curve estimation, object-oriented data analysis, and semiparametric inference. The aim of the ISNPS 2014 conference was to bring together recent advances and trends in several areas of nonparametric statistics in order to facilitate the exchange of research ideas, promote collaboration among researchers from around the globe, and contribute to the further development of the field.