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This paper presents estimates of the parameters involved in a competing risks model in the presence of progressive type- I censored data. We consider the case when the competing risks have generalized inverted exponential distributions. The maximum likelihood method is used to derive point and asymptotic confidence intervals for the unknown parameters. The relative risks due to each cause of failure are investigated. A real data set is used to illustrate the theoretical results and to assess the performance of relative risk and MLE estimates at different schemes of progressively type-I censored samples under causes of failure that follow the generalized inverted exponential distributions.

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