Different Transformation Methods of the Lomax Distribution: A Review
DOI:
https://doi.org/10.62933/6w437q74Keywords:
Lomax distribution, , Inverse Transformation, , power Lomax distribution, , Alpha Power TransformationAbstract
Over the years, several scholars have attempted to create models for occurrences in which the data distribution exhibits varying degrees of heavy-tailedness. Various generalizations or expansions of the Lomax distribution have been suggested in order to achieve this objective. The behavior of the system is determined by two fundamental parameters: the form shape parameter and the scale parameter. The Lomax distribution effectively represents many failure patterns found in real-world situations. The versatility and wide range of applications make it an essential instrument in the investigation of dependability and survival modeling. This paper provides a comprehensive overview of several techniques for extending Lomax distribution. The included extensions include Lomax distribution, Inverse Transformation, and Alpha Power Transformations. Multiple novel and comparable distributions were deliberated and scrutinized. The research has the potential to serve as a valuable standard and encourage the development of improved distributions that can accurately represent complex events.
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