Double Weighted XGamma Distribution for Cancer Survival Data

This article introduces a novel statistical model, the double weighted Xgamma distribution (DWXGD), for analysing cancer survival data. This study investigate its theoretical properties and illustrate its versatility through graphical representations of the probability density and cumulative distribution function for different values of parameters. Parameter estimation is done using the maximum likelihood estimation method. The practical utility of the proposed distribution is illustrated through the use of a real-world leukaemia dataset, in which it consistently outperforms existing models according to –logL, AIC, BIC, AICC, HQIC and CAIC criteria. These findings demonstrate the effectiveness and responsiveness of the DWXGD in modelling skewed or heavily-tailed survival periods, furnishing better forecasts and insightful information for clinical decision-making.