Information Approach for Change Point Analysis of EGGAPE Distribution and Application to COVID-19 Data
)e exponentiated generalized Gull alpha power exponential distribution is an extension of the exponential distribution that can
model data characterized by various shapes of the hazard function. However, change point problem has not been studied for this
distribution. In this study, the change point detection of the parameters of the exponentiated generalized Gull alpha power
exponential distribution is studied using the modified information criterion. In addition, the binary segmentation procedure is
used to identify multiple change point locations. )e assumption is that all the parameters of the EGGAPE distributions are
considered changeable. Simulation study is conducted to illustrate the power of the modified information criterion in detecting
change point in the parameters with different sample sizes. )ree applications related to COVID-19 data are used to demonstrate
the applicability of the MIC in detecting change point in real life scenario.
In this study, the unified hybrid censored approach is employed to estimate the parameters of the inverse Weibull distribution, as well as the survival and hazard rate functions.
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