Inference for confidence sets of the generalized inverted exponential distribution under k-record values

Abstract Based on the k -record values, confidence sets are explored for the parameters of the generalized inverted exponential distribution. Series of exact balanced confidence intervals and exact confidence regions are constructed using pivotal quantities. In order to obtain minimum-size confidence sets, constrained optimization problems are also discussed, and the associated nonlinear programming procedures are established by minimizing Lagrangian functions. Shortest-length confidence intervals and smallest-area confidence regions for the unknown parameters can be obtained by simultaneously solving nonlinear system. Finally, two real data examples and a simulation study are provided for illustrative purposes.