STATISTICAL INFERENCE FOR GEOMETRIC PROCESS WITH THE GENERALIZED RAYLEIGH DISTRIBUTION
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Tarih
2020
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Univ Nis
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In 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.
Açıklama
Anahtar Kelimeler
Monotone processes; non-parametric estimation; parametric estimation; stochastic process; data with trend
Kaynak
Facta Universitatis-Series Mathematics and Informatics
WoS Q Değeri
N/A
Scopus Q Değeri
Cilt
35
Sayı
4
