Förlagets beskrivning
The volume contains articles that should appeal to readers with computational, modeling, theoretical, and applied interests. Methodological issues include parallel computation, Hamiltonian Monte Carlo, dynamic model selection, small sample comparison of structural models, Bayesian thresholding methods in hierarchical graphical models, adaptive reversible jump MCMC, LASSO estimators, parameter expansion algorithms, the implementation of parameter and non-parameter-based approaches to variable selection, a survey of key results in objective Bayesian model selection methodology, and a careful look at the modeling of endogeneity in discrete data settings. Important contemporary questions are examined in applications in macroeconomics, finance, banking, labor economics, industrial organization, and transportation, among others, in which model uncertainty is a central consideration
Fler böcker av författarna
Liknande böcker
Recensioner
Den här boken har tyvärr inte några recensioner ännu. Om du redan läst boken, skriv en recension!
Recensera boken
Skriv en recension och dela dina åsikter med andra. Försök att fokusera på bokens innehåll. Läs våra instruktioner för mer information.
Bayesian Model Comparison
Bokrecensioner » Bayesian Model Comparison
|
|
![Bayesian Model Comparison](/images/background.gif) |
![Bayesian Model Comparison](/images/background.gif) |
|
|
|