The New Extension of Inverse Weibull Distribution with Applications of Medicine Data
محمد إبراهيم, Ø., Almetwally, E. (2021). The New Extension of Inverse Weibull Distribution with Applications of Medicine Data. EKB Journal Management System, 2(العدد الأول - الجزء الأول), 576-597. doi: 10.21608/cfdj.2020.129344
جمال محمد شاکر محمد إبراهيم; Ehab Almetwally. "The New Extension of Inverse Weibull Distribution with Applications of Medicine Data". EKB Journal Management System, 2, العدد الأول - الجزء الأول, 2021, 576-597. doi: 10.21608/cfdj.2020.129344
محمد إبراهيم, Ø., Almetwally, E. (2021). 'The New Extension of Inverse Weibull Distribution with Applications of Medicine Data', EKB Journal Management System, 2(العدد الأول - الجزء الأول), pp. 576-597. doi: 10.21608/cfdj.2020.129344
محمد إبراهيم, Ø., Almetwally, E. The New Extension of Inverse Weibull Distribution with Applications of Medicine Data. EKB Journal Management System, 2021; 2(العدد الأول - الجزء الأول): 576-597. doi: 10.21608/cfdj.2020.129344

The New Extension of Inverse Weibull Distribution with Applications of Medicine Data

المجلة العلمية للدراسات والبحوث المالية والتجارية
Article 18, Volume 2, العدد الأول - الجزء الأول - Serial Number 1, January 2021, Page 576-597  XML PDF (965.95 K)
Document Type: المقالة الأصلية
DOI: 10.21608/cfdj.2020.129344
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Authors
جمال محمد شاکر محمد إبراهيم1; Ehab Almetwallyorcid 2
1المعهد العالي للعلوم الإدارية ببلقاس
2new cairo
Abstract
This paper introduced and studied a new extension of inverse Weibull distribution with three-parameter named as the X-Gamma inverse Weibull (XGIW) distribution. Reliability and hazard rate properties of this distribution are discussed. Maximum likelihood estimation (MLE), maximum product spacing (MPS) Method of the XGIW distribution parameters are discussed. A numerical study using real data analysis and Monte-Carlo simulation are performed to compare between MLE and MPS methods of estimation. The flexibility and potentiality of the XGIW distribution are examined using two real data sets. The cancer data represents remission times (in months) of a random sample of 128 bladder cancer patients and the second data set of leukemia represents 40 patient suffering from leukemia from one of the Ministry of Health Hospitals in Saudi Arabia. The XGIW model can produce better fits than some well-known distributions as generalized inverse Weibull, Kumaraswamy–inverse Weibull, exponentiated generalized inverse Weibull distribution and inverse Weibull distributions.
Keywords
X-Gamma family; inverse Weibull distribution; maximum likelihood estimation; maximum product spacing; data analysis
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