Reliability Estimation for Stress-Strength Model Based on Unit-Half-Normal Distribution

Many lifetime distribution models have successfully served as population for risk analysis and reliability mechanisms. We propose a novel estimation procedure of stress–strength in the case two independent unit-half-normal distributions can fit asymmetrical data with either positive or negative skew, different shape parameters. obtain maximum likelihood estimator reliability, its asymptotic distribution, exact confidence intervals. In addition, intervals model parameters are constructed by using bootstrap techniques. study performance estimators based on Monte Carlo simulations, mean squared error, average bias length, coverage probabilities. Finally, we apply proposed burr measurements iron sheets.