東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Robust and multivariate statistical ...

Yi, Mengxi.

Linked to FindBook

Google Book

Amazon

博客來

Robust and multivariate statistical methods = festschrift in honor of David E. Tyler /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Robust and multivariate statistical methods/ edited by Mengxi Yi, Klaus Nordhausen.
Reminder of title:	festschrift in honor of David E. Tyler /
other author:	Yi, Mengxi.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	xviii, 495 p. :ill. (chiefly col.), digital ;24 cm.
[NT 15003449]:	Part I About David E. Tyler's Publications -- An Analysis of David E. Tyler's Publication and Coauthor Network. A Review of Tyler's Shape Matrix and Its Extensions -- Part II Multivariate Theory and Methods -- On the Asymptotic Behavior of the Leading Eigenvector of Tyler's Shape Estimator Under Weak Identifiability -- On Minimax Shrinkage Estimation with Variable Selection -- On the Finite-Sample Performance of Measure-Transportation-Based Multivariate Rank Tests -- Refining Invariant Coordinate Selection via Local Projection Pursuit -- Directional Distributions and the Half-Angle Principle -- Part III Robust Theory and Methods -- Power M-Estimators for Location and Scatter -- On Robust Estimators of a Sphericity Measure in High Dimension -- Detecting Outliers in Compositional Data Using Invariant Coordinate Selection -- Robust Forecasting of Multiple Time Series with One-Sided Dynamic Principal Components -- Robust and Sparse Estimation of Graphical Models Based on Multivariate Winsorization -- Robustly Fitting Gaussian Graphical Models-the RPackage robFitConGraph -- Robust Estimation of General Linear Mixed Effects Models -- Asymptotic Behaviour of Penalized Robust Estimators in Logistic Regression When Dimension Increases -- Conditional Distribution-Based Downweighting for Robust Estimation of Logistic Regression Models -- Bias Calibration for Robust Estimation in Small Areas -- The Diverging Definition of Robustness in Statistics and Computer Vision -- Part IV Other Methods -- Power Calculations and Critical Values for Two-Stage Nonparametric Testing Regimes -- Data Nuggets in Supervised Learning -- Improved Convergence Rates of Normal Extremes -- Local Spectral Analysis of Qualitative Sequences via Minimum Description Length.
Contained By:	Springer Nature eBook
Subject:	Multivariate analysis. -
Online resource:	https://doi.org/10.1007/978-3-031-22687-8
ISBN:	9783031226878

Robust and multivariate statistical methods = festschrift in honor of David E. Tyler /
Robust and multivariate statistical methodsfestschrift in honor of David E. Tyler /[electronic resource] :edited by Mengxi Yi, Klaus Nordhausen. - Cham :Springer International Publishing :2023. - xviii, 495 p. :ill. (chiefly col.), digital ;24 cm.

Part I About David E. Tyler's Publications -- An Analysis of David E. Tyler's Publication and Coauthor Network. A Review of Tyler's Shape Matrix and Its Extensions -- Part II Multivariate Theory and Methods -- On the Asymptotic Behavior of the Leading Eigenvector of Tyler's Shape Estimator Under Weak Identifiability -- On Minimax Shrinkage Estimation with Variable Selection -- On the Finite-Sample Performance of Measure-Transportation-Based Multivariate Rank Tests -- Refining Invariant Coordinate Selection via Local Projection Pursuit -- Directional Distributions and the Half-Angle Principle -- Part III Robust Theory and Methods -- Power M-Estimators for Location and Scatter -- On Robust Estimators of a Sphericity Measure in High Dimension -- Detecting Outliers in Compositional Data Using Invariant Coordinate Selection -- Robust Forecasting of Multiple Time Series with One-Sided Dynamic Principal Components -- Robust and Sparse Estimation of Graphical Models Based on Multivariate Winsorization -- Robustly Fitting Gaussian Graphical Models-the RPackage robFitConGraph -- Robust Estimation of General Linear Mixed Effects Models -- Asymptotic Behaviour of Penalized Robust Estimators in Logistic Regression When Dimension Increases -- Conditional Distribution-Based Downweighting for Robust Estimation of Logistic Regression Models -- Bias Calibration for Robust Estimation in Small Areas -- The Diverging Definition of Robustness in Statistics and Computer Vision -- Part IV Other Methods -- Power Calculations and Critical Values for Two-Stage Nonparametric Testing Regimes -- Data Nuggets in Supervised Learning -- Improved Convergence Rates of Normal Extremes -- Local Spectral Analysis of Qualitative Sequences via Minimum Description Length.

This book presents recent developments in multivariate and robust statistical methods. Featuring contributions by leading experts in the field it covers various topics, including multivariate and high-dimensional methods, time series, graphical models, robust estimation, supervised learning and normal extremes. It will appeal to statistics and data science researchers, PhD students and practitioners who are interested in modern multivariate and robust statistics. The book is dedicated to David E. Tyler on the occasion of his pending retirement and also includes a review contribution on the popular Tyler's shape matrix.

ISBN: 9783031226878

Standard No.: 10.1007/978-3-031-22687-8doiSubjects--Topical Terms:

517467
Multivariate analysis.

LC Class. No.: QA278

Dewey Class. No.: 519.535

Robust and multivariate statistical methods = festschrift in honor of David E. Tyler /
LDR:03424nmm a2200325 a 4500 001 2317846
003 DE-He213
005 20230419235531.0
006 m d
007 cr nn 008maaau
008 230902s2023 sz s 0 eng d
020 $a 9783031226878 $q (electronic bk.)
020 $a 9783031226861 $q (paper)
024 7 $a 10.1007/978-3-031-22687-8 $2 doi
035 $a 978-3-031-22687-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA278
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.535 $2 23
090 $a QA278 $b .R667 2023
245 0 0 $a Robust and multivariate statistical methods $h [electronic resource] : $b festschrift in honor of David E. Tyler / $c edited by Mengxi Yi, Klaus Nordhausen.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2023.
300 $a xviii, 495 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
505 0 $a Part I About David E. Tyler's Publications -- An Analysis of David E. Tyler's Publication and Coauthor Network. A Review of Tyler's Shape Matrix and Its Extensions -- Part II Multivariate Theory and Methods -- On the Asymptotic Behavior of the Leading Eigenvector of Tyler's Shape Estimator Under Weak Identifiability -- On Minimax Shrinkage Estimation with Variable Selection -- On the Finite-Sample Performance of Measure-Transportation-Based Multivariate Rank Tests -- Refining Invariant Coordinate Selection via Local Projection Pursuit -- Directional Distributions and the Half-Angle Principle -- Part III Robust Theory and Methods -- Power M-Estimators for Location and Scatter -- On Robust Estimators of a Sphericity Measure in High Dimension -- Detecting Outliers in Compositional Data Using Invariant Coordinate Selection -- Robust Forecasting of Multiple Time Series with One-Sided Dynamic Principal Components -- Robust and Sparse Estimation of Graphical Models Based on Multivariate Winsorization -- Robustly Fitting Gaussian Graphical Models-the RPackage robFitConGraph -- Robust Estimation of General Linear Mixed Effects Models -- Asymptotic Behaviour of Penalized Robust Estimators in Logistic Regression When Dimension Increases -- Conditional Distribution-Based Downweighting for Robust Estimation of Logistic Regression Models -- Bias Calibration for Robust Estimation in Small Areas -- The Diverging Definition of Robustness in Statistics and Computer Vision -- Part IV Other Methods -- Power Calculations and Critical Values for Two-Stage Nonparametric Testing Regimes -- Data Nuggets in Supervised Learning -- Improved Convergence Rates of Normal Extremes -- Local Spectral Analysis of Qualitative Sequences via Minimum Description Length.
520 $a This book presents recent developments in multivariate and robust statistical methods. Featuring contributions by leading experts in the field it covers various topics, including multivariate and high-dimensional methods, time series, graphical models, robust estimation, supervised learning and normal extremes. It will appeal to statistics and data science researchers, PhD students and practitioners who are interested in modern multivariate and robust statistics. The book is dedicated to David E. Tyler on the occasion of his pending retirement and also includes a review contribution on the popular Tyler's shape matrix.
650 0 $a Multivariate analysis. $3 517467
650 0 $a Robust statistics. $3 647604
650 0 $a Machine learning. $3 533906
650 1 4 $a Statistical Theory and Methods. $3 891074
650 2 4 $a Multivariate Analysis. $3 788400
650 2 4 $a Applied Statistics. $3 3300946
650 2 4 $a Machine Learning. $3 3382522
700 1 $a Yi, Mengxi. $3 3632376
700 1 $a Nordhausen, Klaus. $3 2162989
700 1 $a Tyler, David E. $3 3632377
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-22687-8
950 $a Mathematics and Statistics (SpringerNature-11649)