Document Type : Original Article
Authors
1
Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, 12613, Egypt
2
Department of Accounting, College of Business, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia
3
Department of Basic Sciences, Higher Institute of Administrative Sciences, Belbeis, AlSharkia, Egypt
4
Department of Mathematics, Faculty of Science, Tanta University, Tanta 31527, Egypt
Abstract
The inverse Ramos-Louzada distribution (IRLD), a novel one-parameter distribution designed to handle real data with hazard rates shaped like an upside-down bathtub, is presented in this work. The IRLD can be used for many applications and has asymmetric and unimodal density shapes. We derive some of the IRLD's main statistical characteristics, such as moments, incomplete moments, inverse moments, probability-weighted moments, quantile functions, extropy measurements, and stochastic ordering.} Focusing on the inference procedures, including the maximum likelihood, the least squares, the weighted least squares, the Cramér-von-Mises, the maximum product of spacing, the Anderson-Darling, the right-tail Anderson-Darling, the left-tailed Anderson-Darling, minimum spacing absolute distance, and minimum spacing absolute log distance, have been used to estimate the parameter of the IRLD. {\color{black} An extensive simulation analysis was performed to compare the performance of various estimates based on some measures of accuracy. Using the partial and general ranks of all estimation methods for various parameter combinations, we show that the maximum likelihood approach is the best estimation strategy, followed by the maximum product of the spacings. We examined real data set to illustrate the potential applications of the proposed distribution. The findings demonstrate that the provided distribution can fit the data more accurately than competing distributions.
Keywords
Main Subjects
)
View on SCiNiTO