Parameter Estimation of the Weighted Generalized Inverse Weibull Distribution
- https://doi.org/10.2991/jsta.d.210607.002How to use a DOI?
- Generalized inverse Weibull distribution, Weighted generalized inverse Weibull distribution, Loss function, Bayesian estimation
Weighted distributions are used widely in many fields of real life such as medicine, ecology, reliability, and so on. The idea of weighted distributions was given by Fisher and studied by Rao in a unified manner who pointed out that in many situations the recorded observations cannot be considered as a random sample from the original distribution. This can be due to nonobservability of some events, damage caused to the original observations or adoption of unequal probability sampling procedure. In this paper, we have proposed weighted version of generalized inverse Weibull distribution known as weighted generalized inverse Weibull distribution (WGIWD). Classical and Bayesian methods of estimation were proposed for estimating the parameters of the new model. The usefulness of the new model was demonstrated by applying it to a real-life data set.
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- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Sofi Mudasir AU - S.P. Ahmad PY - 2021 DA - 2021/07/10 TI - Parameter Estimation of the Weighted Generalized Inverse Weibull Distribution JO - Journal of Statistical Theory and Applications SP - 395 EP - 406 VL - 20 IS - 2 SN - 2214-1766 UR - https://doi.org/10.2991/jsta.d.210607.002 DO - https://doi.org/10.2991/jsta.d.210607.002 ID - Mudasir2021 ER -