Introduction to High-Dimensional Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to High-Dimensional Statistics write by Christophe Giraud. This book was released on 2021-08-25. Introduction to High-Dimensional Statistics available in PDF, EPUB and Kindle. 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.
High-Dimensional Statistics
High-Dimensional Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook High-Dimensional Statistics write by Martin J. Wainwright. This book was released on 2019-02-21. High-Dimensional Statistics available in PDF, EPUB and Kindle. A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.
High-Dimensional Probability
High-Dimensional Probability - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook High-Dimensional Probability write by Roman Vershynin. This book was released on 2018-09-27. High-Dimensional Probability available in PDF, EPUB and Kindle. An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
Statistics for High-Dimensional Data
Statistics for High-Dimensional Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistics for High-Dimensional Data write by Peter Bühlmann. This book was released on 2011-06-08. Statistics for High-Dimensional Data available in PDF, EPUB and Kindle. 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.
Fundamentals of High-Dimensional Statistics
Fundamentals of High-Dimensional Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fundamentals of High-Dimensional Statistics write by Johannes Lederer. This book was released on 2021-11-16. Fundamentals of High-Dimensional Statistics available in PDF, EPUB and Kindle. 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.
