This paper presents Bayesian ways to deal with boundary assessment in the log-straight investigation of meager recurrence tables. The proposed strategies conquer the nonrespectability issues that might happen while applying most extreme probability assessment. A significant moment that utilizing Bayesian strategies is the particular of the earlier appropriations for the model boundaries. We talk about the different potential priors and survey their effect on the boundary assesses by two exact models in which greatest probability assessment gives issues. For the down to earth execution of the Bayesian assessment strategies, we utilized a Metropolis calculation