Introduction To High Dimensional Statistics

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Introduction To High Dimensional Statistics

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Author : Christophe Giraud
language : en
Publisher: CRC Press
Release Date : 2014-12-17

Introduction To High Dimensional Statistics written by Christophe Giraud and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-17 with Business & Economics categories.

Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians

High Dimensional Statistics

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Author : Martin J. Wainwright
language : en
Publisher: Cambridge University Press
Release Date : 2019-02-21

High Dimensional Statistics written by Martin J. Wainwright and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-21 with Business & Economics categories.

A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

Fundamentals Of High Dimensional Statistics

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Author : Johannes Lederer
language : en
Publisher: Springer Nature
Release Date : 2021-11-16

Fundamentals Of High Dimensional Statistics written by Johannes Lederer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-16 with Mathematics categories.

This textbook provides a step-by-step introduction to the tools and principles of high-dimensional statistics. Each chapter is complemented by numerous exercises, many of them with detailed solutions, and computer labs in R that convey valuable practical insights. The book covers the theory and practice of high-dimensional linear regression, graphical models, and inference, ensuring readers have a smooth start in the field. It also offers suggestions for further reading. Given its scope, the textbook is intended for beginning graduate and advanced undergraduate students in statistics, biostatistics, and bioinformatics, though it will be equally useful to a broader audience.

Introduction To Clustering Large And High Dimensional Data

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Author : Jacob Kogan
language : en
Publisher: Cambridge University Press
Release Date : 2007

Introduction To Clustering Large And High Dimensional Data written by Jacob Kogan and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.

Focuses on a few of the important clustering algorithms in the context of information retrieval.

Statistics For High Dimensional Data

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Author : Peter Bühlmann
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-08

Statistics For High Dimensional Data written by Peter Bühlmann and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-08 with Mathematics categories.

Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach highlights the methods’ great potential and practical applicability in a variety of settings. As such, it is a valuable resource for researchers, graduate students and experts in statistics, applied mathematics and computer science.

Algorithmic High Dimensional Robust Statistics

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Author : Ilias Diakonikolas
language : en
Publisher: Cambridge University Press
Release Date : 2023-09-07

Algorithmic High Dimensional Robust Statistics written by Ilias Diakonikolas and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-07 with Computers categories.

This book presents general principles and scalable methodologies to deal with adversarial outliers in high-dimensional datasets.

Functional And High Dimensional Statistics And Related Fields

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Author : Germán Aneiros
language : en
Publisher: Springer Nature
Release Date : 2020-06-19

Functional And High Dimensional Statistics And Related Fields written by Germán Aneiros and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-19 with Mathematics categories.

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.

Principles And Methods For Data Science

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Author :
language : en
Publisher: Elsevier
Release Date : 2020-05-28

Principles And Methods For Data Science written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-28 with Mathematics categories.

Principles and Methods for Data Science, Volume 43 in the Handbook of Statistics series, highlights new advances in the field, with this updated volume presenting interesting and timely topics, including Competing risks, aims and methods, Data analysis and mining of microbial community dynamics, Support Vector Machines, a robust prediction method with applications in bioinformatics, Bayesian Model Selection for Data with High Dimension, High dimensional statistical inference: theoretical development to data analytics, Big data challenges in genomics, Analysis of microarray gene expression data using information theory and stochastic algorithm, Hybrid Models, Markov Chain Monte Carlo Methods: Theory and Practice, and more. - Provides the authority and expertise of leading contributors from an international board of authors - Presents the latest release in the Handbook of Statistics series - Updated release includes the latest information on Principles and Methods for Data Science

Exploration And Analysis Of Dna Microarray And Other High Dimensional Data

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Author : Dhammika Amaratunga
language : en
Publisher: John Wiley & Sons
Release Date : 2014-01-27

Exploration And Analysis Of Dna Microarray And Other High Dimensional Data written by Dhammika Amaratunga and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-27 with Mathematics categories.

Praise for the First Edition “...extremely well written...a comprehensive and up-to-date overview of this important field.” – Journal of Environmental Quality Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition provides comprehensive coverage of recent advancements in microarray data analysis. A cutting-edge guide, the Second Edition demonstrates various methodologies for analyzing data in biomedical research and offers an overview of the modern techniques used in microarray technology to study patterns of gene activity. The new edition answers the need for an efficient outline of all phases of this revolutionary analytical technique, from preprocessing to the analysis stage. Utilizing research and experience from highly-qualified authors in fields of data analysis, Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition features: A new chapter on the interpretation of findings that includes a discussion of signatures and material on gene set analysis, including network analysis New topics of coverage including ABC clustering, biclustering, partial least squares, penalized methods, ensemble methods, and enriched ensemble methods Updated exercises to deepen knowledge of the presented material and provide readers with resources for further study The book is an ideal reference for scientists in biomedical and genomics research fields who analyze DNA microarrays and protein array data, as well as statisticians and bioinformatics practitioners. Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition is also a useful text for graduate-level courses on statistics, computational biology, and bioinformatics.

Sparse Graphical Modeling For High Dimensional Data

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Author : Faming Liang
language : en
Publisher: CRC Press
Release Date : 2023-08-02

Sparse Graphical Modeling For High Dimensional Data written by Faming Liang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-02 with Mathematics categories.

This book provides a general framework for learning sparse graphical models with conditional independence tests. It includes complete treatments for Gaussian, Poisson, multinomial, and mixed data; unified treatments for covariate adjustments, data integration, and network comparison; unified treatments for missing data and heterogeneous data; efficient methods for joint estimation of multiple graphical models; effective methods of high-dimensional variable selection; and effective methods of high-dimensional inference. The methods possess an embarrassingly parallel structure in performing conditional independence tests, and the computation can be significantly accelerated by running in parallel on a multi-core computer or a parallel architecture. This book is intended to serve researchers and scientists interested in high-dimensional statistics, and graduate students in broad data science disciplines. Key Features: A general framework for learning sparse graphical models with conditional independence tests Complete treatments for different types of data, Gaussian, Poisson, multinomial, and mixed data Unified treatments for data integration, network comparison, and covariate adjustment Unified treatments for missing data and heterogeneous data Efficient methods for joint estimation of multiple graphical models Effective methods of high-dimensional variable selection Effective methods of high-dimensional inference