Researchers developed a method to estimate the Erlang distribution using Bayesian shrinkage with Type-II progressive censored data. This method is more manageable than other estimation techniques when prior information about the parameter is available. By comparing different estimation methods, they found that Bayesian shrinkage estimation provides more reliable results. The study used real-life data and simulations to validate the accuracy of the estimates.