Abstract
In this paper, a modified Chi-square goodness-of-fit test called the modified Bagdonavičius-Nikulin goodness-of-fit test statistic is investigated and the applied for distributional validation under the right censored case. The new modified goodness-of-fit test is presented and applied for the right censored data sets. The algorithm of the censored Barzilai-Borwein is employed via a comprehensive simulation study for assessing validity of the new test. The modified Bagdonavičius-Nikulin test is applied to four real and right censored data sets. A new distribution is compared with many other competitive distributions under the new modified Bagdonavičius-Nikulin goodness-of-fit test statistic.
Highlights
Statistical methods for testing the validity of a parametric distribution are in increasing progress
The first data set has reported survival data on 26 psychiatric inpatients admitted to the university of Iowa hospitals during the years 1935-1948
The new modified goodness-of-fit test is presented based on the B-N Chi-square goodness-of-fit test
Summary
Statistical methods for testing the validity of a parametric distribution are in increasing progress. A new modified type Chi-squared goodness-of-fit test statistic which is established based on the wellknown B-N test is presented and applied for distributional validation under the exponentiated Rayleigh exponentiated Nadarajah-Haghighi model using the right censored case. Yousof et al (2021c) introduced new modified Chi-square test for the right the censoring distributional validation under a novel Nadarajah Haghighi model with some new characterization results and different estimation methods. Another new version for the right censored validity under a new Chen model with some applications in reliability and medicine is presented by Ibrahim et al (2021)
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