Matrix tricks for linear statistical models : our personal top twenty
In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very f...
Na minha lista:
| Auteurs principaux: | , , |
|---|---|
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado em: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
2011.
Cham : Springer Nature |
| Acesso em linha: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Matrix Tricks for Linear Statistical Models, Texte imprimé, 9783642104725 • Matrix Tricks for Linear Statistical Models, Texte imprimé, 9783642104749 • Matrix Tricks for Linear Statistical Models, Texte imprimé, 9783642447594 |
Sumário:
- Introduction
- Easy Column Space Tricks
- Easy Projector Tricks
- Easy Correlation Tricks
- Generalized Inverses in a Nutshell
- Rank of the Partitioned Matrix and the Matrix Product
- Rank Cancellation Rule
- Sum of Orthogonal Projector
- Minimizing cov(y - Fx)
- BLUE
- General Solution to AYB = C
- Invariance with Respect to the Choice of Generalized Inverse
- Block-Diagonalization and the Schur Complement
- Nonnegative Definiteness of a Partitioned Matrix
- The Matrix M
- Disjointness of Column Spaces
- Full Rank Decomposition
- Eigenvalue Decomposition
- Singular Value Decomposition
- The Cauchy-Schwarz Inequality
- Notation
- References
- Author Index
- Subject Index.