Bicer, CenkerBicer, Hayrinisa D.Kara, MahmutYilmaz, Asuman2025-01-212025-01-2120200352-96652406-047Xhttps://doi.org/10.22190/FUMI2004107Bhttps://hdl.handle.net/20.500.12587/25483In the present paper, the statistical inference problem is considered for the geometric process (GP) by assuming the distribution of the first arrival time with generalized Rayleigh distribution with the parameters alpha and lambda. We have used the maximum likelihood method for obtaining the ratio parameter of the GP and distributional parameters of the generalized Rayleigh distribution. By a series of Monte-Carlo simulations evaluated through the different samples of sizes - small, moderate and large, we have also compared the estimation performances of the maximum likelihood estimators with the other estimators available in the literature such as modified moment, modified L-moment, and modified least squares. Furthermore, wehave presented two real-life datasets analyses to show the modeling behavior of GP with generalized Rayleigh distribution.eninfo:eu-repo/semantics/openAccessMonotone processes; non-parametric estimation; parametric estimation; stochastic process; data with trendArticle3541107112510.22190/FUMI2004107BWOS:000615256700016N/A