Mixture of Shanker Distributions: Estimation, Simulation and Application

The Shanker distribution, a one-parameter lifetime distribution with an increasing hazard rate function, is recommended by for modelling lifespan data. In this study, we examine the theoretical and practical implications of 2-component mixture model (2-CMSM). A significant feature proposed model’s function that it has rising, decreasing, upside-down bathtub forms. We investigate statistical characteristics mixed model, such as probability-generating factorial-moment-generating cumulants, characteristic Mills ratio, mean residual life, time to failure. There graphic representation density, mean, functions, coefficient variation, skewness, kurtosis. Our final approach estimate parameters using appropriate approaches maximum likelihood, least squares, weighted squares. Using simulation analysis, examined how estimates behaved graphically. results demonstrated that, in majority cases, likelihood have smallest square errors among all other estimates. Finally, observed when sample size rises, precision measures decrease estimation techniques, indicating are consistent. Through two real data analyses, suggested validity adaptability contrasted those models, including exponential distributions Lindley .