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

Rolando de la Cruz, Hugo S. Salinas, Cristian Meza

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


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

Original languageEnglish
Article number837
Issue number4
StatePublished - Apr 2022
Externally publishedYes


  • bootstrap confidence intervals
  • bootstrap methods
  • entropy
  • exact and asymptotic confidence interval
  • mean residual life
  • simulation studies
  • strength–stress model
  • unit-half-normal distribution


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