Functional And High Dimensional Statistics And Related Fields

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Functional and High-Dimensional Statistics and Related Fields

Germán Aneiros,Ivana Horová,Marie Hušková,Philippe Vieu
Functional and High Dimensional Statistics and Related Fields Book PDF

Author : Germán Aneiros,Ivana Horová,Marie Hušková,Philippe Vieu
Publisher : Springer Nature
Page : 254 pages
File Size : 54,8 Mb
Release : 2020-06-19
Category : Mathematics
ISBN : 9783030477561

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Functional and High-Dimensional Statistics and Related Fields by Germán Aneiros,Ivana Horová,Marie Hušková,Philippe Vieu Pdf

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.

Functional Statistics and Related Fields

Germán Aneiros,Enea G. Bongiorno,Ricardo Cao,Philippe Vieu
Functional Statistics and Related Fields Book PDF

Author : Germán Aneiros,Enea G. Bongiorno,Ricardo Cao,Philippe Vieu
Publisher : Springer
Page : 288 pages
File Size : 50,9 Mb
Release : 2017-04-25
Category : Mathematics
ISBN : 9783319558462

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Functional Statistics and Related Fields by Germán Aneiros,Enea G. Bongiorno,Ricardo Cao,Philippe Vieu Pdf

This volume collects latest methodological and applied contributions on functional, high-dimensional and other complex data, related statistical models and tools as well as on operator-based statistics. It contains selected and refereed contributions presented at the Fourth International Workshop on Functional and Operatorial Statistics (IWFOS 2017) held in A Coruña, Spain, from 15 to 17 June 2017. The series of IWFOS workshops was initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008. Since then, many of the major advances in functional statistics and related fields have been periodically presented and discussed at the IWFOS workshops.

High-Dimensional Statistics

Martin J. Wainwright
High Dimensional Statistics Book PDF

Author : Martin J. Wainwright
Publisher : Cambridge University Press
Page : 571 pages
File Size : 51,6 Mb
Release : 2019-02-21
Category : Business & Economics
ISBN : 9781108498029

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High-Dimensional Statistics by Martin J. Wainwright Pdf

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

Introduction to High-Dimensional Statistics

Christophe Giraud
Introduction to High Dimensional Statistics Book PDF

Author : Christophe Giraud
Publisher : CRC Press
Page : 410 pages
File Size : 52,7 Mb
Release : 2021-08-25
Category : Computers
ISBN : 9781000408355

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Introduction to High-Dimensional Statistics by Christophe Giraud Pdf

Praise for the first edition: "[This book] succeeds singularly at providing a structured introduction to this active field of research. ... it is arguably the most accessible overview yet published of the mathematical ideas and principles that one needs to master to enter the field of high-dimensional statistics. ... recommended to anyone interested in the main results of current research in high-dimensional statistics as well as anyone interested in acquiring the core mathematical skills to enter this area of research." —Journal of the American Statistical Association Introduction to High-Dimensional Statistics, Second Edition preserves the philosophy of the first edition: to be a concise guide for students and researchers discovering the area and interested in the mathematics involved. The main concepts and ideas are presented in simple settings, avoiding thereby unessential technicalities. High-dimensional statistics is a fast-evolving field, and much progress has been made on a large variety of topics, providing new insights and methods. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics, this new edition: Offers revised chapters from the previous edition, with the inclusion of many additional materials on some important topics, including compress sensing, estimation with convex constraints, the slope estimator, simultaneously low-rank and row-sparse linear regression, or aggregation of a continuous set of estimators. Introduces three new chapters on iterative algorithms, clustering, and minimax lower bounds. Provides enhanced appendices, minimax lower-bounds mainly with the addition of the Davis-Kahan perturbation bound and of two simple versions of the Hanson-Wright concentration inequality. Covers cutting-edge statistical methods including model selection, sparsity and the Lasso, iterative hard thresholding, aggregation, support vector machines, and learning theory. Provides detailed exercises at the end of every chapter with collaborative solutions on a wiki site. Illustrates concepts with simple but clear practical examples.

Statistics for High-Dimensional Data

Peter Bühlmann,Sara van de Geer
Statistics for High Dimensional Data Book PDF

Author : Peter Bühlmann,Sara van de Geer
Publisher : Springer Science & Business Media
Page : 568 pages
File Size : 51,8 Mb
Release : 2011-06-08
Category : Mathematics
ISBN : 9783642201929

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Statistics for High-Dimensional Data by Peter Bühlmann,Sara van de Geer Pdf

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.

High-Dimensional Probability

Roman Vershynin
High Dimensional Probability Book PDF

Author : Roman Vershynin
Publisher : Cambridge University Press
Page : 299 pages
File Size : 52,8 Mb
Release : 2018-09-27
Category : Business & Economics
ISBN : 9781108415194

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High-Dimensional Probability by Roman Vershynin Pdf

An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

High-Dimensional Statistics

Martin J. Wainwright
High Dimensional Statistics Book PDF

Author : Martin J. Wainwright
Publisher : Cambridge University Press
Page : 571 pages
File Size : 49,7 Mb
Release : 2019-02-21
Category : Mathematics
ISBN : 9781108571234

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High-Dimensional Statistics by Martin J. Wainwright Pdf

Recent years have witnessed an explosion in the volume and variety of data collected in all scientific disciplines and industrial settings. Such massive data sets present a number of challenges to researchers in statistics and machine learning. This book provides a self-contained introduction to the area of high-dimensional statistics, aimed at the first-year graduate level. It includes chapters that are focused on core methodology and theory - including tail bounds, concentration inequalities, uniform laws and empirical process, and random matrices - as well as chapters devoted to in-depth exploration of particular model classes - including sparse linear models, matrix models with rank constraints, graphical models, and various types of non-parametric models. With hundreds of worked examples and exercises, this text is intended both for courses and for self-study by graduate students and researchers in statistics, machine learning, and related fields who must understand, apply, and adapt modern statistical methods suited to large-scale data.

Fundamentals of High-Dimensional Statistics

Johannes Lederer
Fundamentals of High Dimensional Statistics Book PDF

Author : Johannes Lederer
Publisher : Springer Nature
Page : 355 pages
File Size : 45,6 Mb
Release : 2021-11-16
Category : Mathematics
ISBN : 9783030737924

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Fundamentals of High-Dimensional Statistics by Johannes Lederer Pdf

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.

Functional and Operatorial Statistics

Sophie Dabo-Niang,Frédéric Ferraty
Functional and Operatorial Statistics Book PDF

Author : Sophie Dabo-Niang,Frédéric Ferraty
Publisher : Springer Science & Business Media
Page : 296 pages
File Size : 46,5 Mb
Release : 2008-05-21
Category : Mathematics
ISBN : 9783790820621

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Functional and Operatorial Statistics by Sophie Dabo-Niang,Frédéric Ferraty Pdf

An increasing number of statistical problems and methods involve infinite-dimensional aspects. This is due to the progress of technologies which allow us to store more and more information while modern instruments are able to collect data much more effectively due to their increasingly sophisticated design. This evolution directly concerns statisticians, who have to propose new methodologies while taking into account such high-dimensional data (e.g. continuous processes, functional data, etc.). The numerous applications (micro-arrays, paleo- ecological data, radar waveforms, spectrometric curves, speech recognition, continuous time series, 3-D images, etc.) in various fields (biology, econometrics, environmetrics, the food industry, medical sciences, paper industry, etc.) make researching this statistical topic very worthwhile. This book gathers important contributions on the functional and operatorial statistics fields.

Contributions in infinite-dimensional statistics and related topics

Enea G. Bongiorno,Ernesto Salinelli,Aldo Goia,Philippe Vieu
Contributions in infinite dimensional statistics and related topics Book PDF

Author : Enea G. Bongiorno,Ernesto Salinelli,Aldo Goia,Philippe Vieu
Publisher : Società Editrice Esculapio
Page : 300 pages
File Size : 48,6 Mb
Release : 2014-05-21
Category : Mathematics
ISBN : 9788874887637

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Contributions in infinite-dimensional statistics and related topics by Enea G. Bongiorno,Ernesto Salinelli,Aldo Goia,Philippe Vieu Pdf

The interest towards Functional and Operatorial Statistics, and, more in general, towards infinite-dimensional statistics has dramatically increased in the statistical community and in many other applied scientific areas where people faces functional data. This volume collects the works selected and presented at the Third Edition of the International Workshop on Functional and Operatorial Statistics held in Stresa, Italy, from the 19th to the 21st of June 2014 (IWFOS’2014). The meeting represents an opportunity of bringing together leading researchers active on these topics both for what concerns theoretical aspects and a wide range of applications in various fields. To promote collaborations with other important strictly related areas of infinite-dimensional Statistics, such as High Dimensional Statistics and Model Selection Procedures, this book hosts works in the latter research subjects too.

Analysis of Multivariate and High-Dimensional Data

Inge Koch
Analysis of Multivariate and High Dimensional Data Book PDF

Author : Inge Koch
Publisher : Cambridge University Press
Page : 531 pages
File Size : 47,8 Mb
Release : 2014
Category : Business & Economics
ISBN : 9780521887939

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Analysis of Multivariate and High-Dimensional Data by Inge Koch Pdf

This modern approach integrates classical and contemporary methods, fusing theory and practice and bridging the gap to statistical learning.

Big and Complex Data Analysis

S. Ejaz Ahmed
Big and Complex Data Analysis Book PDF

Author : S. Ejaz Ahmed
Publisher : Springer
Page : 386 pages
File Size : 46,5 Mb
Release : 2017-03-21
Category : Mathematics
ISBN : 9783319415734

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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.

Recent Advances in Functional Data Analysis and Related Topics

Frédéric Ferraty
Recent Advances in Functional Data Analysis and Related Topics Book PDF

Author : Frédéric Ferraty
Publisher : Springer Science & Business Media
Page : 322 pages
File Size : 47,6 Mb
Release : 2011-06-15
Category : Mathematics
ISBN : 9783790827361

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Recent Advances in Functional Data Analysis and Related Topics by Frédéric Ferraty Pdf

New technologies allow us to handle increasingly large datasets, while monitoring devices are becoming ever more sophisticated. This high-tech progress produces statistical units sampled over finer and finer grids. As the measurement points become closer, the data can be considered as observations varying over a continuum. This intrinsic continuous data (called functional data) can be found in various fields of science, including biomechanics, chemometrics, econometrics, environmetrics, geophysics, medicine, etc. The failure of standard multivariate statistics to analyze such functional data has led the statistical community to develop appropriate statistical methodologies, called Functional Data Analysis (FDA). Today, FDA is certainly one of the most motivating and popular statistical topics due to its impact on crucial societal issues (health, environment, etc). This is why the FDA statistical community is rapidly growing, as are the statistical developments . Therefore, it is necessary to organize regular meetings in order to provide a state-of-art review of the recent advances in this fascinating area. This book collects selected and extended papers presented at the second International Workshop of Functional and Operatorial Statistics (Santander, Spain, 16-18 June, 2011), in which many outstanding experts on FDA will present the most relevant advances in this pioneering statistical area. Undoubtedly, these proceedings will be an essential resource for academic researchers, master students, engineers, and practitioners not only in statistics but also in numerous related fields of application.

Nonparametric Functional Data Analysis

Frédéric Ferraty,Philippe Vieu
Nonparametric Functional Data Analysis Book PDF

Author : Frédéric Ferraty,Philippe Vieu
Publisher : Springer Science & Business Media
Page : 260 pages
File Size : 52,6 Mb
Release : 2006-11-22
Category : Mathematics
ISBN : 9780387366203

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Nonparametric Functional Data Analysis by Frédéric Ferraty,Philippe Vieu Pdf

Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data exploration. This book links these two fields of modern statistics by explaining how functional data can be studied through parameter-free statistical ideas. At the same time it shows how functional data can be studied through parameter-free statistical ideas, and offers an original presentation of new nonparametric statistical methods for functional data analysis.

Statistical Foundations of Data Science

Jianqing Fan,Runze Li,Cun-Hui Zhang,Hui Zou
Statistical Foundations of Data Science Book PDF

Author : Jianqing Fan,Runze Li,Cun-Hui Zhang,Hui Zou
Publisher : CRC Press
Page : 752 pages
File Size : 50,6 Mb
Release : 2020-09-21
Category : Mathematics
ISBN : 9781466510852

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Statistical Foundations of Data Science by Jianqing Fan,Runze Li,Cun-Hui Zhang,Hui Zou Pdf

Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.