Open AccessThe extended Burr-R class: properties, applications and modified test for censored data
Author(s) -
Abdulhakim A. Al-Babtain,
Rehan Ahmad Khan Sherwani,
Ahmed Z. Afify,
Khaoula Aidi,
M. Arslan Nasir,
Farrukh Jamal,
Abdus Saboor
Publication year - 2021
Publication title -
aims mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.329
H-Index - 15
ISSN - 2473-6988
DOI - 10.3934/math.2021176
Subject(s) - statistic , lomax distribution , mathematics , statistics , maximum likelihood , chi square test , class (philosophy) , test statistic , square (algebra) , statistical hypothesis testing , computer science , artificial intelligence , geometry
This article introduces a new three-parameter Marshall-Olkin Burr-R (MOB-R) family which extends the generalize Burr-G class. Some of its general properties are discussed. One of its special models called the MOB-Lomax distribution is studied in detail for illustrative purpose. A modified chi-square test statistic is provided for right censored data from the MOB-L distribution. The model parameters are estimated via the maximum likelihood and simulation results are obtained to assess the behavior of the maximum likelihood approach. Applications to real data sets are provided to show the usefulness of the proposed MOB-Lomax distribution. The modified chi-square test statistic shows that the MOB-Lomax model can be used as a good candidate for analyzing real censored data.