Iranian Statistical Society Journal of the Iranian Statistical Society 1726-4057 24 2 2025 12 01 Influence diagnostics for the Gamma-Pareto regression: a DFFITS-based comparison of residuals 69 90 733693 10.22034/jirss.2026.2076260.1154 EN Nasir Saleem Department of Statistics, Bahauddin Zakariya university, Multan Pakistan. 0000-0001-6556-4737 Atif Akbar Department of Statistics, Bahauddin Zakariya University (BZU), Multan, Pakistan,60800 0000-0003-3227-9731 Asad Abbas Department of Statistics Bahauddin Zakariya University (BZU), Multan, Pakistan,60800 Journal Article 2025 10 30 The generalized linear models (GLMs) use Gamma-Pareto regression Model (G-PRM) to address the sensitivity of influential observations. Difference of Fits (DFFITS) is a popular technique for identifying influential observations. We apply DFFITS to the G-PRM with various residuals. We present illustrative real and simulated data. One class of adjusted Pearson residuals is more effective in detecting influential observations, considering small or large dispersion parameters. We calculate detection percentages to evaluate the proposed procedure's performance, replicating the process 10,000 times.<br><br>The generalized linear models (GLMs) use Gamma-Pareto regression Model (G-PRM) to address the sensitivity of influential observations. Difference of Fits (DFFITS) is a popular technique for identifying influential observations. We apply DFFITS to the G-PRM with various residuals. We present illustrative real and simulated data. One class of adjusted Pearson residuals is more effective in detecting influential observations, considering small or large dispersion parameters. We calculate detection percentages to evaluate the proposed procedure's performance, replicating the process 10,000 times. https://jirss.irstat.ir/article_733693_e1035396534d80dc520be81afe6b3cd0.pdf