In degradation analysis, stochastic process–based models are classical tools that allow to make inferences about the lifetime of highly reliable products. These models rely on assumptions that can be restrictive in terms of the probability distributions imposed on stochastic increments and fail in describing complex dependence structures in real-world degradation datasets. By relaxing the restrictive assumptions, increment degradation models represent flexible and widely applicable extensions of traditional stochastic models. This course focuses on modeling dependencies among increments with particular emphasis on the use of pair-copula decompositions. This course also introduces general techniques to improve lifetime estimation and prediction.

藉由學術論文學習相關性增量衰退量模型相關知識

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