We present a methodology for estimation, prediction, and model assessment of vector autoregressive moving-average (VARMA) models in the Bayesian framework using Markov chain Monte Carlo algorithms. The sampling-based Bayesian framework for inference allows for the incorporation of parameter restrict
Bayesian analysis of constant elasticity of variance models
β Scribed by Jennifer S. K. Chan; S. T. Boris Choy; Anna B. W. Lee
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 212 KB
- Volume
- 23
- Category
- Article
- ISSN
- 1524-1904
- DOI
- 10.1002/asmb.639
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
A layered elastic model is adopted in the paper for the analysis of soil layering e!ects on the results of Cone Penetration Testing (CPT). Analytical solutions associated with the layered elastic CPT model and obtained via numerically integrating the fundamental singular solution for layered elastic
This paper considers a common problem in analysis of variance where the responses to a set of treatments are nominal (i.e. are recorded in frequencies) with no underlying metric. Reasoning by analogy from standard analysis of variance of a two-way classification we develop chi-square tests for signi