Covariance Analysis and Beyond

Wei Lan () and Chih-Ling Tsai ()
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Wei Lan: Southwestern University of Finance and Economics, School of Statistics and Data Science and Center of Statistical Research
Chih-Ling Tsai: University of California - Davis, Graduate School of Management

in Springer Books from Springer

Date: 2026
ISBN: 978-3-032-08796-6
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Chapters in this book:

Ch Chapter 1 Introduction

Wei Lan and Chih-Ling Tsai

Ch Chapter 10 Tensor and Covariance Matrices

Wei Lan and Chih-Ling Tsai

Ch Chapter 2 Covariance Matrices, Precision (Concentration) Matrices, Estimation, and Tests

Wei Lan and Chih-Ling Tsai

Ch Chapter 3 Structured Covariance Matrices and Unconstrained Parameterization

Wei Lan and Chih-Ling Tsai

Ch Chapter 4 Covariance Regression Models

Wei Lan and Chih-Ling Tsai

Ch Chapter 5 Covariance-Mean Regression Models

Wei Lan and Chih-Ling Tsai

Ch Chapter 6 Fixed and Random Covariance Models

Wei Lan and Chih-Ling Tsai

Ch Chapter 7 Spatial Autoregressive and Network Autocorrelation Models

Wei Lan and Chih-Ling Tsai

Ch Chapter 8 Factor Models and Covariance Matrices

Wei Lan and Chih-Ling Tsai

Ch Chapter 9 Machine Learning and Covariance Matrices

Wei Lan and Chih-Ling Tsai

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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprbok:978-3-032-08796-6

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DOI: 10.1007/978-3-032-08796-6

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