References

In this work, we consider a new extension of the one-dimensional stochastic gamma diffusion process (cf. [2]) by introducing external time functions as exogenous factors, in the same way the exogenous factors have been introduced in the lognormal and Gompertz processes (cf. [3]), Gompertz process (cf. [1] ) and Vasicek process (cf. [4]). Firstly, we determine the probabilistic characteristics of the studied process as the analytical expression of the process, its transition probability density function and their trend functions. Secondly, we study the statistical inference in this process: we estimate the parameters present in the model by using the maximum likelihood estimation method in basis of the discreet sampling of the process, thus obtaining the expression of the likelihood estimators and their properties (statistical distributions, sufficiency and completeness), then, the confidence intervals of the parameters