A new modified model with application to engineering data sets

Abstract

This paper introduces a new three-parameter distribution called the modified Kies Gompertz (MKGO) distribution to identify an effective statistical distribution in a real-life modeling data set. The distribution’s probability density function may take numerous forms and graphs, and it could be negatively and positively skewed and uni-modal. We established several statistical properties of the MKGO distribution, such as moments, skewness, kurtosis, moment generating function, distribution of order statistic, quantile function, stress strength reliability and two cases of entropy measures. Further, we proposed six methods for estimating the unknown parameters of the suggested model. A brief Monter Carlo (MC) simulation study is illustrated in terms of average estimate (AE) and mean square error (MSE). to show the efficiency of these estimators. Finally, we analyzed four real data sets in the engineering sector to evaluate the potential of the proposed model with that of various existing distributions.