(untitled) (Statistics, Optimization & Information Computing, 2025)
In this paper we propose non-parametric estimates for the information measure entropy when a progressively Type-I interval censored data is available. Different non-parametric approaches are used for deriving the estimates. Entropy-based tests of exponentiality are proposed. The critical values and the power values of the proposed tests are simulated and studied under various alternatives. Real life data sets are presented and analysed.