Formulas useful for linear regression analysis and related matrix theory : It's only formulas but we like them
This is an unusual book because it contains a great deal of formulas. Hence it is a blend of monograph, textbook, and handbook. It is intended for students and researchers who need quick access to useful formulas appearing in the linear regression model and related matrix theory. This is not a regul...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Livre numérique |
| Sprache: | Anglais |
| Veröffentlicht: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Ausgabe: | 1st ed. 2013. |
| Schriftenreihe: | SpringerBriefs in Statistics
|
| Online Zugang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Anmerkung: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Formulas useful for linear regression analysis and related matrix theory, It's Only Formulas But We Like Them, by Simo Puntanen, Jarkko Isotalo, George P.H. Styan, Berlin, Springer, 2013, 1 vol. (XII-125 pages), SpringerBriefs in statistics, 978-3-642-32930-2 • Formulas Useful for Linear Regression Analysis and Related Matrix Theory, Texte imprimé, 9783642329326 • Formulas useful for linear regression analysis and related matrix theory, It's Only Formulas But We Like Them, by Simo Puntanen, Jarkko Isotalo, George P.H. Styan, Berlin, Springer, 2013, 1 vol. (XII-125 pages), SpringerBriefs in statistics, 978-3-642-32930-2 |
Inhaltsangabe:
- The Model Matrix Fitted Values and Residuals Regression Coefficients Alternative Estimators Decompositions of Sums of Squares Partial Correlations Distributions Testing Hypotheses Diagnostics BLUE: Some Helpful Identities Estimability Best Linear Unbiased Estimator The Watson Efficiency Linear Sufficiency and Admissibility Best Linear Unbiased Predictor Mixed Model Multivariate Linear Model Inverse of a Partitioned Matrix Generalized Inverses Projectors Eigenvalues Discriminant Analysis Factor Analysis Canonical Correlations Matrix Decompositions Principal Component Analysis Löwner Ordering Rank Rules Inequalities Kronecker Product Matrix Derivatives