Bayesian and Classical Inference for the Generalized Log-Logistic Distribution with Applications to Survival Data.

ABSTRACT: The generalized log-logistic distribution is especially useful for modelling survival data with variable hazard rate shapes because it extends the log-logistic distribution by adding an extra parameter to the classical distribution, resulting in greater flexibility in analyzing and modelling various data types. We derive the fundamental mathematical and statistical properties of the proposed distribution in this paper. Many well-known lifetime special submodels are included in the proposed distribution, including the Weibull, log-logistic, exponential, and Burr XII distributions. The maximum likelihood method was used to estimate the unknown parameters of the proposed distribution, and a Monte Carlo simulation study was run to assess the estimators' performance. This distribution is signif

SUBMITTER: Muse AH 

PROVIDER: S-EPMC8523281 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature