Sine power Burr X distribution with estimation and applications in physics and other fields

Abstract This article aims to introduce a new three-parameter lifetime distribution called sine power Burr X (SPB-X) distribution. The proposed distribution is obtained by the sine-G class of distributions and the power Burr X distribution. Various properties of the proposed distribution, including explicit expressions for the quantile function, Bowley skewness, Moors kurtosis, ordinary moments, generating function, incomplete and conditional moments, and some numerical and graphical illustrations, are provided. Some various significant reliability metrics for the SPB-X model, including common reliability functions, mean residual life function, mean waiting time function, residual moment, and reversed residual life. Several essential risk measures for the SPB-X distribution. These risk measures include the value at risk, the expected shortfall, the tail value at risk, the tail variance, and the tail variance premium. Four estimation methods were employed to estimate the model’s parameters such as maximum likelihood, least squares, maximum product spacing, and Bayesian. A simulation study is conducted to assess the performance of the estimation methods. Finally, five real data are considered to analyze the usefulness and flexibility of the proposed model.