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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.

Lomax inverse Weibull model: properties, applications, and a modified Chi-squared goodness-of-fit test for validation