Improving Weibull distribution estimation for generalized Type I censored data using modified SMOTE

James K. Starling, Christina Mastrangelo and Youngjun Choe

Reliability Engineering and System Safety, 2021, vol. 211, issue C

Abstract: In reliability analysis, lifetime data may be heavily censored and this censoring can have an adverse effect on parameter estimates. Using maximum-likelihood estimation (MLE) to estimate the parameters of reliability functions is common in practice especially with (right) censored observations. However, estimating parameters using MLE introduces an inherent bias which tends to increase as the number of observations decreases and/or the censoring proportion increases. Reliability demonstration tests (RDT) typically use a Type I or Type II censoring mechanism; however, in many real-life applications a generalized Type I censoring mechanism, where each observation has its own censoring times, is often more applicable. These examples occur in structural risk analyses, obsolescence predictions, and medical studies where items under study may have different introduction dates but have lifetimes from the same probability distribution. This research improves Weibull distribution parameter estimates by combining a modified MLE and an oversampling method. Empirical results are presented with recommendations for preferred oversampling sizes, dependent upon the sample size and censoring proportion, using the Kullback–Leibler divergence to measure the difference between the known distribution and estimated distributions. A case study is provided to highlight the method’s use in an obsolescence prediction application.

Keywords: Maximum likelihood estimation (MLE); Censored data; Kullback–Leibler divergence; Bias correction; Oversampling; Synthetic minority oversampling technique (SMOTE) (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832021000661
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:211:y:2021:i:c:s0951832021000661

DOI: 10.1016/j.ress.2021.107505

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().