상세정보
Export to Refworks부가기능
Introduction to high-dimensional statistics
상세 프로파일
| 자료유형 | 단행본 |
|---|---|
| 서명/저자사항 | Introduction to high-dimensional statistics/ Christophe Giraud. |
| 개인저자 | Giraud, Christophe,author. |
| 형태사항 | 1 online resource. |
| 총서사항 | Monographs on statistics & applied probability;139 |
| 기타형태 저록 | Print version: 9781482237948 Print version: Giraud, Christophe. Introduction to high-dimensional statistics. Boca Raton : CRC Press, Taylor & Francis Group, [2015] 9781482237948 |
| ISBN | 9781482237955 1482237954 1322629536 9781322629537 |
| 서지주기 | Includes bibliographical references and index. |
| 내용주기 | Chapter 1: Introduction -- Chapter 2: Model Selection -- Chapter 3: Aggregation of Estimators -- Chapter 4: Convex Criteria -- Chapter 5: Estimator Selection -- Chapter 6: Multivariate Regression -- Chapter 7: Graphical Models -- Chapter 8: Multiple Testing -- Chapter 9: Supervised Classification. |
| 요약 | 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 and data analysts and has required the development of new statistical methods capable of separating the signal from the noise. Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for handling high-dimensional data. The book is intended to expose the reader to the key concepts and ideas in the most simple settings possible while avoiding unnecessary technicalities. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics, this highly accessible text: Describes the challenges related to the analysis of high-dimensional data Covers cutting-edge statistical methods including model selection, sparsity and the lasso, aggregation, and learning theory Provides detailed exercises at the end of every chapter with collaborative solutions on a wikisite Illustrates concepts with simple but clear practical examples Introduction to High-Dimensional Statistics is suitable for graduate students and researchers interested in discovering modern statistics for massive data. It can be used as a graduate text or for self-study. |
| 일반주제명 | Dimensional analysis. Multivariate analysis. Big data. Statistics. MATHEMATICS --Applied. MATHEMATICS --Probability & Statistics --General. Big data. Dimensional analysis. Multivariate analysis. Statistics. Boosting Datenanalyse Hochdimensionale Daten Inferenzstatistik Lasso-Methode Mathematische Modellierung Statistik |
| 언어 | 영어 |
| 바로가기 |  |
