Examining censored sampling models for some distributions

Survival analysis plays a crucial role in disciplines such as medicine, engineering, and social sciences, encompassing statistical methods that examine the timing of specific events. However, censored datasets limit the effectiveness of traditional analysis methods due to missing or unobserved information. In this study, parameter estimation for censored data is evaluated using parametric approaches. The first section of the study presents a literature review on parameter estimation for distributions in the context of censored data. The second section addresses the basic definitions and concepts, while the third section provides information about censoring. The final section discusses in detail the parameter estimation of commonly used distributions in survival analysis for censored data.