GIBBS SAMPLING ON A STEADY MODEL

In this study Gibbs sampling, a widely used simulation method, is ap-plied to the steady model, a simple variation of the dynamic linear model, and the model parameters are estimated. The estimates ob-tained from Gibbs sampling and the results for the standard Kalman ¯lter are compared and are found to be close. These similarities in the results indicate the success of the stochastic simulation. In this study, a variance modulation on the steady model is also applied and Gibbs sampling is proposed to overcome analytic problems. In the variance adaptation, de¯ned as abt (a; b> 0), estimates for the model parame-ters are obtained for di®erent values of a and b