Discriminating between the Lognormal and Weibull Distributions under Progressive Censoring

Yıl 2019, Cilt: 40 Sayı: 2, 493 - 504, 30.06.2019

Coşkun Kuş Ahmet Pekgör İsmail Kınacı

https://doi.org/10.17776/csj.470148

Cited By: 2

Öz

In this paper, the ratio of maximized likelihood and
Minimized Kullback-Leibler Divergence methods are discussed for discrimination
between log-normal and Weibull distributions. The progressive Type-II right
censored sample is considered in the study. The probability of correct
selections is simulated and compared to investigate the performance of the
procedures for different censoring schemes and parameter settings.

Anahtar Kelimeler

Discrimination, Log-normal distribution, Power analysis, Simulation, Progressive type-II right censoring

İlerleyen Tür Sansür Altında Lognormal ve Weibull Dağılımlarının Ayrımı

Öz

Bu çalışmada, log-normal ve weibull dağılımları arasında ayırım için en
çok olabilirlik oran ve Kullback-Leibler uzaklık metotları tartışılmıştır.
Çalışmada, ilerleyen tür sansürlü veri durumu ele alınmıştır. Doğru seçim
oranları hesaplanmış ve farklı parametre ve sansür şemaları altında testlerin
performansları karşılaştırılmıştır.

Anahtar Kelimeler

Ayırım, Log-normal dağılım, Güç analizi, Simülasyon, İlerleyen tür sansürleme

Kaynakça

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