Comparison of Estimation Methods for Inverse Weibull Distribution

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Akgül F. G., Şenoğlu B.

Trends and Perspectives in Linear Statistical Inference . Contributions to Statistics, Müzgan Tez,Dietrich von Rosen, Editör, Springer, London/Berlin , İstanbul, ss.1-22, 2018

  • Yayın Türü: Kitapta Bölüm / Araştırma Kitabı
  • Basım Tarihi: 2018
  • Yayınevi: Springer, London/Berlin 
  • Basıldığı Şehir: İstanbul
  • Sayfa Sayıları: ss.1-22
  • Editörler: Müzgan Tez,Dietrich von Rosen, Editör
  • Karadeniz Teknik Üniversitesi Adresli: Hayır

Özet

The aim of this chapter is to estimate unknown parameters of inverse

Weibull (IW) distribution using eight different estimation methods: maximum

likelihood (ML), least squares (LS), weighted least squares (WLS), percentile (PC),

maximum product of spacing (MPS), probability weighted moments (PWM),

Cramér–von Mises (CM), and Anderson-Darling (AD). The performances of these

estimation methods are compared via an extensive Monte Carlo simulation study.

Their robustness properties are also investigated. At the end of the study, two real

data sets are analyzed for illustration and comparison purposes.