Poster abstract details
Bayesian determination of ejection models
We study the structure and kinematics of the AGN jet components from VLBI observations. One of the primary estimates in the study is the ejection epoch, i.e., the time when a superluminal jet component was ejected from the radio core. Linear regression is the widely used method to estimate the ejection epoch which is ideally the x-intercept obtained from fitting a straight line. Obtaining the errors or confidence interval on the x-intercept is a known calibration problem. We appoach this problem from the Bayesian perspective with the use of the MultiNest sampling algorithm.