Journal
RELIABILITY ENGINEERING & SYSTEM SAFETY
Volume 207, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2020.107327
Keywords
Heterogeneity; Two-dimensional data analysis; Copula; Global dependence; Local dependence
Funding
- National Natural Science Foundation of China [51675025]
- National Key RD of China [2016YFB0100400]
- Academic Excellence Foundation of BUAA for PhD Students
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This paper conducts a two-dimensional warranty analysis on data with heterogeneity in terms of both age and usage. Two models are developed to evaluate the severity of warranty claims, with different dependence structures. It is found that over 85% of claims are classified as normal failures, and local dependence structures may vary.
This paper conducts a two-dimensional warranty analysis on the data with heterogeneity in terms of both age and usage. Two models are developed to evaluate the severity of warranty claims. The first one uses a copula to describe the global dependence between the age and usage populations, whereas the second one further captures various local dependence in different warranty regions. Since the mixing proportions regarding heterogeneity are latent, the expectation maximization algorithm is proposed to estimate parameters and classify the warranty data. The likelihood ratio test is further utilized to determine the number of subpopulations. A comparison with two other models shows the superiority of the proposed one in terms of the Akaike information criterion. It is found that more than 85% of the claims are classified into normal failures, and local dependence structures might vary from a symmetric one to an asymmetric one. Meanwhile, as the sample size decreases, the heterogeneity of usage would vanish, and some local dependence structures would change.
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