Bayesian Analysis of Vector ARMA Models using Gibbs Sampling

Production Forecasting of Taiwan's Technology Industrial Cluster: A Bayesian Autoregression Approach

“…Logarithmic transformation can be found in Kadiyala and Karlsson (1997) and Simpson et al (2001). Preliminary deseasonalization can also be found in Doan, Litterman, and Sims (1984), Kumar et al (1995), Ray (1993, Ravishanker andRay (1997). Salazar and Weale (1999).…”

“…This means that we used the census X-1 1 additive method first to produce deseasonalized series. Such a predeseasonalization is preferable in the BVAR model structure because a series with a seasonal factor will produce significance in high-lag coefficients that makes inefficient parameterization (e.g., Doan, 1992;Hamilton, 1994;Ravishanker & Ray, 1997).…”

Bayesian Subset Model Selection for Time Series

“…This can be computed based on an MCMC output as , where { ψ j , j = 1, …, M } is an MCMC realisation. A measure similar to this was proposed by Ravishanker and Ray (1997). Based on a burn‐in of 1000 sweeps and with a gap of 20 iterations thereafter, Bayesian forecast errors were computed for the SG and subset models with thinned sample of size M = 100; smaller burn‐in was used only for quicker computation.…”

Vector AutoRegressive Moving Average Models: A Review

“…Albassam, Soliman, and Ali ( 2023) conduct a wide simulation study to investigate the effectiveness of this proposal. Ravishanker and Ray (1997) consider Bayesian estimation of VARMA models using Metropolis Hastings to obtain samples from the joint posterior density of the VARMA parameters based on the exact Gaussian likelihood, the VARMA model is identified using Bayesian variable selection techniques.…”