By Tanizaki Hisashi, Xingyuan Zhang
During this paper, we convey the right way to use Bayesian procedure within the multiplicative heteroscedasticity version mentioned through . The Gibbs sampler and the Metropolis-Hastings (MH) set of rules are utilized to the multiplicative heteroscedasticity version, the place a few candidate-generating densities are thought of within the MH set of rules. we supply out Monte Carlo examine to check the homes of the estimates through Bayesian strategy and the normal opposite numbers similar to the changed two-step estimator (M2SE) and the utmost probability estimator (MLE). Our result of Monte Carlo learn exhibit that the candidate-generating density selected in our paper is acceptable, and Bayesian method exhibits larger functionality than the normal opposite numbers within the criterion of the basis suggest sq. errors (RMSE) and the interquartile diversity (IR).