MAXIMUM LQ-LIKELIHOOD ESTIMATION FOR THE PARAMETERS OF MARSHALL-OLKIN EXTENDED BURR XII DISTRIBUTION

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Atıf İçin Kopyala

ÖZDEMİR Ş., GÜNEY Y., TUAÇ Y., ARSLAN O.

COMMUNICATIONS FACULTY OF SCIENCES UNIVERSITY OF ANKARA-SERIES A1 MATHEMATICS AND STATISTICS, cilt.68, sa.1, ss.17-34, 2019 (ESCI)

• Yayın Türü: Makale / Tam Makale
• Cilt numarası: 68 Sayı: 1
• Basım Tarihi: 2019
• Doi Numarası: 10.31801/cfsuasmas.443579
• Dergi Adı: COMMUNICATIONS FACULTY OF SCIENCES UNIVERSITY OF ANKARA-SERIES A1 MATHEMATICS AND STATISTICS
• Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), TR DİZİN (ULAKBİM)
• Sayfa Sayıları: ss.17-34
• Anahtar Kelimeler: Marshall-Olkin extended Burr XII (MOEBXII) distribution, maximum Lq estimation, maximum likelihood estimator, FAILURE MODEL
• Ankara Üniversitesi Adresli: Evet

Özet

Marshall-Olkin extended Burr XII (MOEBXII) distribution is proposed by Al-Saiari et al. (2014) to obtain a more flexible family of distributions. Some estimation methods like maximum likelihood, Bayes and M estimations are used to estimate the parameters of the MOEBXII distribution in literature. In this paper, we propose to use Maximum Lq (MLq) estimation method to find alternative estimators for the parameters of the MOEBXII distribution. We give some simulation studies and a real data example to compare the performance of the MLq estimators with the maximum likelihood and M estimators. According to our results MLq estimation method is a good alternative to the maximum likelihood and M estimation methods in the presence of outliers.