Assessing the efficiency of maximum likelihood, interquartile range, and Monte Carlo methods for estimating Weibull distribution parameters
DOI:
https://doi.org/10.56947/amcs.v26.449Keywords:
Breast Cancer, Interquartile Range, Monte Carlo Estimation, Sensitivity Analysis, WinsorizationAbstract
This study compares three statistical methods such as Maximum Likelihood Estimation (MLE), Interquartile Range (IQR) Estimation, and Monte Carlo Estimation in survival data analysis using the Weibull distribution. The primary objective is to assess each method's robustness, sensitivity to outliers, and computational efficiency. The research focuses on breast cancer survival data obtained from Lagos State University Teaching Hospital, Nigeria, and explores the effectiveness of each technique in the presence of censored data. Sensitivity analysis reveals how parameter changes influence model accuracy. Results indicate that MLE is sensitive to data characteristics, while IQR Estimation offers robustness against outliers. Monte Carlo Estimation demonstrates flexibility but shows computational complexity in handling skewed data.
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