Asymptotically Normal Estimators for the Parameters of the Gamma-Exponential Distribution

Currently, much research attention has focused on generalizations of known mathematical objects in order to obtain adequate models describing real phenomena. An important role the applied theory probability and statistics is gamma class distributions, which proven be a convenient effective tool for modeling many processes. The quite wide includes distributions that have useful properties such as, example, infinite divisibility stability, makes it possible use from this as asymptotic approximations various limit theorems. One most tasks estimates parameters model distribution available data. In paper, we consider gamma-exponential distribution, generalization class. Estimators some are given, normality these estimators proven. When obtaining estimates, modified method moments was used, based logarithmic calculated basis Mellin transform generalized distribution. On results obtained, confidence intervals estimated constructed. work can used study probabilistic continuous with an unbounded non-negative support.