Abstract

In this study, we introduce a novel extension of the exponential distribution known as the Sine Type II Topp-Leone Exponential (STIITLEx) distribution. We derive key properties of this distribution, including the quantile function, survival function, moments, moment-generating function, and entropy. Parameter estimation is performed using the maximum likelihood estimation method, and a comprehensive simulation study was conducted to evaluate the estimator's consistency. Our simulation results confirmed the estimator's consistency, as indicated by diminishing bias and root mean square error (RMSE) with increasing sample sizes. Applying the model to two real-world datasets, we compare its performance against existing models with a common baseline. Our findings demonstrate that the STIITLEx model offers a superior fit to the datasets across all seven evaluation metrics considered.

Key words: Exponential distribution, moments, maximum likelihood estimation, covid19 dataset