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Matrix Algebra from a Statistician's Perspective
Abstract
Preface. - Matrices. - Submatrices and partitioned matricies. - Linear dependence and independence. - Linear spaces: row and column spaces. - Trace of a (square) matrix. - Geometrical considerations. - Linear systems: consistency and compatability. - Inverse matrices. - Generalized inverses. - Indepotent matrices. - Linear systems: solutions. - Projections and projection matrices. - Determinants. - Linear, bilinear, and quadratic forms. - Matrix differentiation. - Kronecker products and the vec and vech operators. - Intersections and sums of subspaces. - Sums (and differences) of matrices. - Minimzation of a second-degree polynomial (in n variables) subject to linear constraints. - The Moore-Penrose inverse. - Eigenvalues and Eigenvectors. - Linear transformations. - References. - Index.
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Cited by
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Data association in stochastic mapping using the joint compatibility test
Neira, J., & Tardos, J. D. (2001) · IEEE Transactions on Robotics and Automation · doi:10.1109/70.976019 · Cited by 772
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Giannone, D., Lenza, M., & Primiceri, G. E. (2015) · Review of Economics and Statistics · doi:10.1162/rest_a_00483 · Cited by 710
Bayesian approach to extended object and cluster tracking using random matrices
Koch, J. W. (2008) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2008.4655362 · Cited by 667
Metadata
- Authors
- Ziegel, E. R., & Harville, D. A.
- Venue
- Technometrics
- Publisher
- JSTOR
- Published
- 1998-05
- Volume
- 40
- Issue
- 2
- Pages
- 164
- ISSN
- 0040-1706 (ISSN-L)
- OpenAlex
- W2101950184
- Cited by
- 880
- References
- 0
- FWCI
- 13.56
- Type
- journal article
- Language
- en
- Open access
- closed
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