The repository administrator has not yet configured an RDF license.
MOMENT, CUMULANT, DAN CHARACTERISTIC FUNCTION DARI GENERALIZED EXPONENTIAL DISTRIBUTION
The generalized exponential distribution (GED) proposed by Gupta and Kundu (1999) is an important lifetime distribution in survival analysis. Generalized Exponential Distribution is defined as a particular case of Gompertz-Velhust distribution function when ρ=1. It has two parameters, α as a shape parameter and λ as a scale parameter. Actually, it can be a regular exponential distribution if the value of the shape parameter equals to one. Generalized Exponential Distribution is a distribution that also has the characteristics of the population. In this study discuss about characteristics of generalized exponential distribution (GED) especially moment, cumulants, and characteristic function. The moments and cumulant generating function of generalized exponential distribution (GED) can be obtained using moment generating function. Subsequently, by using cumulant generating function, we can get cumulants which can be used to find skewness and kurtosis. Furthermore, we obtained characteristic function by using probability density function and proof that the norm of characteristic function is equals to one. It was show that generalized exponential distribution (GED) is monotone function. Finally, to show it is either increasing monotonic or decreasing monotonic function, the probability density function (PDF), skewness and kurtosis were simulated by using mathlab. Keyword: Generalized Exponential Distribution, Moment, Cumulant, and Characteristic Function.
MOMENT, CUMULANT, DAN CHARACTERISTIC FUNCTION DARI GENERALIZED EXPONENTIAL DISTRIBUTION (File PDF)
MOMENT, CUMULANT, DAN CHARACTERISTIC FUNCTION DARI GENERALIZED EXPONENTIAL DISTRIBUTION (Other)
HTML Summary of #4062 MOMENT, CUMULANT, DAN CHARACTERISTIC FUNCTION DARI GENERALIZED EXPONENTIAL DISTRIBUTION