High Dimensional Statistics

This book PDF is perfect for those who love Business & Economics genre, written by Martin J. Wainwright and published by Cambridge University Press which was released on 21 February 2019 with total hardcover pages 571. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related High Dimensional Statistics books below.

High Dimensional Statistics
Author : Martin J. Wainwright
File Size : 45,9 Mb
Publisher : Cambridge University Press
Language : English
Release Date : 21 February 2019
ISBN : 9781108498029
Pages : 571 pages
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High Dimensional Statistics by Martin J. Wainwright Book PDF Summary

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

High Dimensional Statistics

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

Get Book
Statistics for High Dimensional Data

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.

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Introduction to High Dimensional Statistics

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

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Fundamentals of High Dimensional Statistics

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,

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High Dimensional Probability

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

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High Dimensional Data Analysis with Low Dimensional Models

Connects fundamental mathematical theory with real-world problems, through efficient and scalable optimization algorithms.

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Analysis of Multivariate and High Dimensional Data

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

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Statistical Analysis for High Dimensional Data

This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications.

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