Estimation of parameters of the loglogistic distribution based on progressive censoring using the EM algorithm
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Dosyalar
Tarih
2006
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Although the maximum likelihood estimation method based on pro- gressively censored data has been studied extensively, traditionally the Newton-Raphson method has been used to obtain the estimates (Ng et al., 2002). As pointed out by Little and Rubin in 1983, the EM algorithm will converge reliably but rather slowly (as compared to the Newton-Raphson method) when the amount of information in the missing data is relatively large. Therefore, in this study, maximum likelihood estimates for the parameters of the Loglogistic distribution are obtained using the EM algorithm based on a progressive Type-II right censored sample. An illustrative example is also given.
Açıklama
Anahtar Kelimeler
İstatistik ve Olasılık, Matematik
Kaynak
Hacettepe Journal of Mathematics and Statistics
WoS Q Değeri
Scopus Q Değeri
Cilt
35
Sayı
2
Künye
Kuş, C., Kaya, M. F. (2006). Estimation of parameters of the loglogistic distribution based on progressive censoring using the EM algorithm. Hacettepe Journal of Mathematics and Statistics, 35(2), 203-211.
