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