Statistical Inference on Sine-Exponential Distribution Parameter - Adepoju, Akeem Ajibola; Bello, Akanji Olalekan; Isa, Alhaji Modu; Adesupo, Akinrefon; Olumoh, Jamiu S. (UUM Press, 2024)
The Sine-Exponential (Sine-E) distribution is a probability distribu tion that combines the periodic behavior of the sine function with the decay characteristic of the exponential function. This study addresses the problem of identifying the most accurate and reliable estimation method for the parameter of the Sine-E distribution. The objective is to evaluate various parameter estimation techniques, including Maxi-mum Likelihood Estimation (MLE), Least Squares Estimation (LSE), Weighted Least Squares Estimation (WLSE), Maximum Product of Spacing Estimation (MPSE), Cramer-von-Mises Estimation (CVME), and Anderson-Darling Estimation (ADE), using Mean Square Error (MSE) as the criterion for determining the technique with the mini-mum error. The study’s fndings reveal that as sample size increases, the parameter estimates for all techniques converge to the true param eter value, with decreases in bias, MSE, and mean relative estimates. Among the techniques evaluated, the MPSE method consistently pro-vides estimates closest to the true parameter value and exhibits the least bias and lowest MSE across small, moderate, and large sample sizes, making it the best estimator for the Sine-E distribution