Lomax inverse Weibull model: properties, applications, and a modified Chi-squared goodness-of-fit test for validation
By Hafida Goual, Haitham M. Yousof, M. Masoom Ali. 2020
62 citations recorded by the source corpus.
In this paper, we introduce a new extension of the Inverse Weibull distribution along with a number of its mathematical properties. Next, we construct a modified Chi-squared goodness-of-fit test based on the Nikulin-Rao-Robson statistic for censored and complete data. We describe the theory and the mechanism of the Y2 n test statistic which can be used in survival and reliability data analysis. We use the maximum likelihood estimators based on the initial non grouped data sets. Then, we conduct numerical simulations to reinforce the results. For showing the applicability of our model in various fields, we illustrate the proposed test by applications to two real data sets for complete data case and two other data sets in the presence of right censored.
Subfields: Polymers and Plastics, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/c90d71fd2f8ac915373d7d4bee883db1eb8f8f37
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Statistics and Probability
Citations in the corpus
- A Generalization of Lomax Distribution with Properties, Copula and Real Data Applications (2020, background): “Recently, many useful extensions are presented by Bhatti et al. (2018), Goual Yousof (2019), Ibrahim and Yousof (2020), Karamikabir et al. (2020), Mansour et al. (2020f), Ansari et al. (2020), Goual et al. (2020) and Yadav et al. (2020).”