The article discusses different ways to estimate parameters of a specific distribution called Poisson Nadarajah-Haghighi (PNH). The researchers looked at ten methods, including maximum likelihood and Bayesian approaches, and compared their performance using simulations. They found that weighted least squares and maximum product spacing estimators had the least biases and errors, but Bayesian estimates were the most accurate overall. The study also applied these methods to a real-world data set to show how they can be used in practice.