| VOLUME 01 —
Matrix Algebra (by Karim Abadir and Jan Magnus) (2005) |
| 1. |
Vectors |
| 2. |
Matrices |
| 3. |
Vector spaces |
| 4. |
Rank, inverse, and determinant |
| 5. |
Partitioned matrices |
| 6. |
Systems of equations |
| 7. |
Eigenvalues, eigenvectors, and factorizations |
| 8. |
Positive (semi)definite and idempotent matrices |
| 9. |
Matrix functions |
| 10. |
Kronecker product, vec-operator, and Moore-Penrose inverse |
| 11. |
Patterned matrices: Commutations, and duplication matrix |
| 12. |
Matrix inequalities |
| 13. |
Matrix calculus |
|
Appendix A: Some mathematical tools |
|
Appendix B: Notation |
|
Corrections
and additions (9/25/2006)
|
| VOLUME 07 —
Bayesian Econometric Methods (by Gary Koop, Dale J. Poirier, Justin L. Tobias) (2007) |
| 1. |
The subjective interpretation of probability |
| 2. |
Bayesian inference |
| 3. |
Point estimation |
| 4. |
Frequentist properties of Basyesian estimators |
| 5. |
Interval estimation |
| 6. |
Hypothesis testing |
| 7. |
Prediction |
| 8. |
Choice of prior |
| 9. |
Asymptotic Bayes |
| 10. |
The linear regression model |
| 11. |
Basics of Bayesian computation |
| 12. |
Hierarchical models |
| 13. |
The linear regression model with general covariance matrix |
| 14. |
Latent variable models |
| 15. |
Mixture models |
| 16. |
Bayesian model averaging and selection |
| 17. |
Some stationary time series models |
| 18. |
Some nonstationary time series models |
|
Appendix |
