Topological And Statistical Methods For Complex Data
Download Topological And Statistical Methods For Complex Data full books in PDF, epub, and Kindle. Read online free Topological And Statistical Methods For Complex Data ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Topological and Statistical Methods for Complex Data
Author | : Janine Bennett,Fabien Vivodtzev,Valerio Pascucci |
Publsiher | : Springer |
Total Pages | : 297 |
Release | : 2014-11-19 |
Genre | : Mathematics |
ISBN | : 9783662449004 |
Download Topological and Statistical Methods for Complex Data Book in PDF, Epub and Kindle
This book contains papers presented at the Workshop on the Analysis of Large-scale, High-Dimensional, and Multi-Variate Data Using Topology and Statistics, held in Le Barp, France, June 2013. It features the work of some of the most prominent and recognized leaders in the field who examine challenges as well as detail solutions to the analysis of extreme scale data. The book presents new methods that leverage the mutual strengths of both topological and statistical techniques to support the management, analysis, and visualization of complex data. It covers both theory and application and provides readers with an overview of important key concepts and the latest research trends. Coverage in the book includes multi-variate and/or high-dimensional analysis techniques, feature-based statistical methods, combinatorial algorithms, scalable statistics algorithms, scalar and vector field topology, and multi-scale representations. In addition, the book details algorithms that are broadly applicable and can be used by application scientists to glean insight from a wide range of complex data sets.
Advances in Complex Data Modeling and Computational Methods in Statistics
Author | : Anna Maria Paganoni,Piercesare Secchi |
Publsiher | : Springer |
Total Pages | : 210 |
Release | : 2014-11-04 |
Genre | : Mathematics |
ISBN | : 9783319111490 |
Download Advances in Complex Data Modeling and Computational Methods in Statistics Book in PDF, Epub and Kindle
The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.
Topological Methods in Data Analysis and Visualization IV
Author | : Hamish Carr,Christoph Garth,Tino Weinkauf |
Publsiher | : Springer |
Total Pages | : 363 |
Release | : 2017-06-01 |
Genre | : Mathematics |
ISBN | : 9783319446844 |
Download Topological Methods in Data Analysis and Visualization IV Book in PDF, Epub and Kindle
This book presents contributions on topics ranging from novel applications of topological analysis for particular problems, through studies of the effectiveness of modern topological methods, algorithmic improvements on existing methods, and parallel computation of topological structures, all the way to mathematical topologies not previously applied to data analysis. Topological methods are broadly recognized as valuable tools for analyzing the ever-increasing flood of data generated by simulation or acquisition. This is particularly the case in scientific visualization, where the data sets have long since surpassed the ability of the human mind to absorb every single byte of data. The biannual TopoInVis workshop has supported researchers in this area for a decade, and continues to serve as a vital forum for the presentation and discussion of novel results in applications in the area, creating a platform to disseminate knowledge about such implementations throughout and beyond the community. The present volume, resulting from the 2015 TopoInVis workshop held in Annweiler, Germany, will appeal to researchers in the fields of scientific visualization and mathematics, domain scientists with an interest in advanced visualization methods, and developers of visualization software systems.
Topological Data Analysis for Scientific Visualization
Author | : Julien Tierny |
Publsiher | : Springer |
Total Pages | : 150 |
Release | : 2018-01-16 |
Genre | : Mathematics |
ISBN | : 9783319715070 |
Download Topological Data Analysis for Scientific Visualization Book in PDF, Epub and Kindle
Combining theoretical and practical aspects of topology, this book provides a comprehensive and self-contained introduction to topological methods for the analysis and visualization of scientific data. Theoretical concepts are presented in a painstaking but intuitive manner, with numerous high-quality color illustrations. Key algorithms for the computation and simplification of topological data representations are described in detail, and their application is carefully demonstrated in a chapter dedicated to concrete use cases. With its fine balance between theory and practice, "Topological Data Analysis for Scientific Visualization" constitutes an appealing introduction to the increasingly important topic of topological data analysis for lecturers, students and researchers.
Classification and Multivariate Analysis for Complex Data Structures
Author | : Bernard Fichet,Domenico Piccolo,Rosanna Verde,Maurizio Vichi |
Publsiher | : Springer Science & Business Media |
Total Pages | : 460 |
Release | : 2011-03-04 |
Genre | : Mathematics |
ISBN | : 9783642133121 |
Download Classification and Multivariate Analysis for Complex Data Structures Book in PDF, Epub and Kindle
The growing capabilities in generating and collecting data has risen an urgent need of new techniques and tools in order to analyze, classify and summarize statistical information, as well as to discover and characterize trends, and to automatically bag anomalies. This volume provides the latest advances in data analysis methods for multidimensional data which can present a complex structure: The book offers a selection of papers presented at the first Joint Meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society. Special attention is paid to new methodological contributions from both the theoretical and the applicative point of views, in the fields of Clustering, Classification, Time Series Analysis, Multidimensional Data Analysis, Knowledge Discovery from Large Datasets, Spatial Statistics.
Geometric and Topological Inference
Author | : Jean-Daniel Boissonnat,Frédéric Chazal,Mariette Yvinec |
Publsiher | : Cambridge University Press |
Total Pages | : 247 |
Release | : 2018-09-27 |
Genre | : Computers |
ISBN | : 9781108419390 |
Download Geometric and Topological Inference Book in PDF, Epub and Kindle
A rigorous introduction to geometric and topological inference, for anyone interested in a geometric approach to data science.
Computational Topology for Data Analysis
Author | : Tamal Krishna Dey,Yusu Wang |
Publsiher | : Cambridge University Press |
Total Pages | : 455 |
Release | : 2022-03-10 |
Genre | : Computers |
ISBN | : 9781009098168 |
Download Computational Topology for Data Analysis Book in PDF, Epub and Kindle
This book provides a computational and algorithmic foundation for techniques in topological data analysis, with examples and exercises.
Functional and High Dimensional Statistics and Related Fields
Author | : Germán Aneiros,Ivana Horová,Marie Hušková,Philippe Vieu |
Publsiher | : Springer Nature |
Total Pages | : 254 |
Release | : 2020-06-19 |
Genre | : Mathematics |
ISBN | : 9783030477561 |
Download Functional and High Dimensional Statistics and Related Fields Book in PDF, Epub and Kindle
This book presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing methodological and computational aspects, as well as real-world applications. It covers topics like classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operatorial statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis, and includes applications in automobile engineering, criminology, drawing recognition, economics, environmetrics, medicine, mobile phone data, spectrometrics and urban environments. The book gathers selected, refereed contributions presented at the Fifth International Workshop on Functional and Operatorial Statistics (IWFOS) in Brno, Czech Republic. The workshop was originally to be held on June 24-26, 2020, but had to be postponed as a consequence of the COVID-19 pandemic. Initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008, the IWFOS workshops provide a forum to discuss the latest trends and advances in functional statistics and related fields, and foster the exchange of ideas and international collaboration in the field.