Stochastic process–based degradation models are widely used in the reliability literature. Increment degradation models extend these stochastic frameworks by relaxing the traditional additive property. As empirical models, they offer the flexibility to explore alternative distributions for degradation increments, allowing for a more comprehensive and adaptable representation of degradation behavior. This course focuses on modeling dependencies among increments, with particular emphasis on the use of copula functions. It also addresses the challenges arising from the loss of additivity, especially those related to the construction of likelihood functions and the prediction of lifetime distributions.

培養與訓練衰退量資料分析能力與相關統計推論

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