Bayesian Estimation for Inverse-Gaussian Distribution under Square Error Loss Function

In this paper, with no closed-form Bayes estimators available, Lindley's approximation is taken into consideration when trying to estimate the parameters of the inverse Gaussian distribution. We shall only take into account the squared error loss function. When both the location and scale parameters have different prior distributions, this applies Lindley's approximation to the suggested Bayesian treatment of the inverse Gaussian distribution. Introduces the Bayesian treatment's simulated results. And A simulation study using Mathematica 12 is used to explain numerous numerical situations and show how well estimators function.