Applied Directional Statistics by Christophe Ley
This book describes new data-driven methodologies and case studies.The primary targeted audience is researchers in statistics, as well as those in fundamental roles such as earth sciences, environmetrics, astrophysics, machine learning, image analysis and bioinformatics.-
Statistical and Econometric Methods for Transportation Data Analysis
- Bayesian Computational Methods in Statistical Signal Processing
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Age-Period-Cohort Analysis
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Measurement Error
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Clinical Trials in Oncology
- Compositional Data Analysis in Practice
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Bayesian Analysis of Capture-Recapture Data with Hidden Markov Models
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Survival Analysis with Interval-Censored Data
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Statistics for Fission Track Analysis
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Analysis of Capture-Recapture Data
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Missing Data Analysis in Practice
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Power Analysis of Trials with Multilevel Data
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Bayesian Analysis for Population Ecology
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Statistical Methods in Epilepsy
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An Invariant Approach to Statistical Analysis of Shapes
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Bayesian Disease Mapping
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Modern Directional Statistics
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Statistical Methods in Psychiatry and Related Fields
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Statistics of Medical Imaging
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Capture-Recapture Methods for the Social and Medical Sciences
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Multiple Imputation of Missing Data in Practice
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Bayesian Modeling of Spatio-Temporal Data with R
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Clinical Trials in Oncology, Third Edition
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Correspondence Analysis in Practice
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Introduction to Computational Biology
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Model-based Geostatistics for Global Public Health
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Design of Experiments for Generalized Linear Models
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Statistics for Biological Networks
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Parameter Redundancy and Identifiability
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Model-Based Monitoring and Statistical Control
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Flexible Imputation of Missing Data, Second Edition
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The Data Book
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Mendelian Randomization
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Statistical Analysis of Questionnaires
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Design and Analysis of Quality of Life Studies in Clinical Trials
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Statistical Detection and Surveillance of Geographic Clusters
I would recommend Applied Directional Statistics to anyone who has a received graduate-level training in statistics and is interested in directional dataThis book provides a wide variety of data examples that broadens readers’ horizon on the applicability of directional data. The methods described in this book are easy to follow and they all have connections with similar methods in Euclidean data. For instance, the directional kernel density estimator in Chapter 9 and 11 is closely related to the usual kernel density estimator in Euclidean space. These chapters serve as good reading references of a regular statistics course.
- Yen-Chi Chen, THE AMERICAN STATISTICIAN 2021, VOL. 75, NO. 3, 354
Christophe Ley is professor of mathematical statistics at Ghent University. His research interests include semi-parametrically efficient inference, flexible modeling, directional statistics, sport 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 of the International Statistical Institute. He is associate editor for the journals Computational Statistics & Data Analysis, Annals of the Institute of Statistical Mathematics, 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.
| SKU | Unavailable |
| ISBN 13 | 9780367733452 |
| ISBN 10 | 0367733455 |
| Title | Applied Directional Statistics |
| Author | Christophe Ley |
| Series | Chapman And Hall Crc Interdisciplinary Statistics |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Taylor & Francis Ltd |
| Year published | 2020-12-18 |
| Number of pages | 316 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |