Sampling Plan for the Kavya–Manoharan Generalized Inverted Kumaraswamy Distribution with Statistical Inference and Applications

In this article, we introduce the Kavya–Manoharan generalized inverse Kumaraswamy (KM-GIKw) distribution, which can be presented as an improved version of distribution with three parameters. It contains numerous referenced lifetime distributions literature and a large panel new ones. Among essential features attributes covered in our research are quantiles, moments, information measures. particular, various entropy measures (Rényi, Tsallis, etc.) derived discussed numerically. The adaptability KM-GIKw terms shapes probability density hazard rate functions demonstrates how well it is able to fit different types data. Based on it, acceptance sampling plan created when life test truncated at predefined time. More precisely, truncation time intended represent median preset factors. separate part, focus put inference distribution. related parameters estimated using Bayesian, maximum likelihood, product spacings methods. For Bayesian method, both symmetric asymmetric loss employed. To examine behaviors estimates based criterion measurements, Monte Carlo simulation carried out. Finally, aim demonstrating applicability findings, real datasets used. results show that offers superior fits compared other well-known distributions.