A Bayesian Simulation Approach to Inference on a Multi-State Latent Factor Intensity Model
This paper provides a Bayesian approach to inference on a multi-state latent factor intensity model to manage the problem of highly analytically intractable pdfs. The sampling algorithm used to obtain posterior distributions of the model parameters includes a particle filter step and a Metropolis-Hastings step within a Gibbs sampler. A simulated example is conducted to show the feasibility and accuracy of this sampling algorithm. The approach is applied to the case of credit ratings transition matrices.
Year of publication: |
2008-08
|
---|---|
Authors: | Chua, Chew Lian ; Lim, G. C. ; Smith, Penelope |
Institutions: | Melbourne Institute of Applied Economic and Social Research (MIAESR), Faculty of Business and Economics |
Saved in:
freely available
Saved in favorites
Similar items by person
-
Chua, Chew Lian, (2007)
-
Regional Indexes of Activity: Combining the Old with the New
Claus, Edda, (2011)
-
A Bayesian simulation approach to inference on a multi-state latent factor intensity
Chua, Chew Lian, (2008)
- More ...