| Description |
1 online resource (xv, 350 pages) : illustrations |
| Contents |
Machine derived contents note: Chapter 1: Decision Theory and Bayesian Inference -- Chapter 2: Bayesian Statistics and Linear Regression -- Chapter 3: Methods of Numerical Integration -- Chapter 4: Prior Densities for the Regression Model -- Chapter 5: Dynamic Regression Models -- Chapter 6: Bayesian Unit Roots -- Chapter 7: Heteroskedasticity and ARCH -- Chapter 8: Nonlinear Tome Series Models -- Chapter 9: Systems of Equations -- Appendix A: Probability Distributions -- Appendix B: Generating Random Numbers |
| Summary |
Offering an up-to-date coverage of the basic principles and tools of Bayesian inference in economics, this textbook then shows how to use Bayesian methods in a range of models suited to the analysis of macroeconomic and financial time series |
| Bibliography |
Includes bibliographical references and index |
| Subject |
Bayesian statistical decision theory.
|
|
Econometric models.
|
|
Bayesian statistical decision theory.
|
|
Econometric models.
|
| Form |
Electronic book
|
| Author |
Lubrano, Michel
|
|
Richard, Jean-François, 1943-
|
| ISBN |
9780191695315 |
|
0191695319 |
|
