Quantile-based Fréchet half logistic distribution and its Bayesian inference

Key Points

• Bayesian inference yields robust posterior estimates for the Fréchet distribution parameters, highlighting its flexibility.
• The study incorporates quantile-based methods to improve estimation accuracy and demonstrate their effectiveness, with clear benefits over traditional approaches.
• Observational analysis using quantile frameworks reveals significant improvements in parameter estimation for complex datasets.
• Implications for statistical modeling are promising, particularly in fields requiring advanced probabilistic methods.