Reliability estimation for inverse rayleigh distribution in the presence of outliers / Mustafa Ali Mustafa Taha ; Supervised Abdallah Mohamed Abdelfattah

Thesis (M.Sc.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Mathematical Statistics

Reliability analysis is the of major developmental factors, to evaluate electronic component or system reliability. Reliability is the probability that a product or service will be provided properly for a specified period of time (design life) under the design operating conditions (such as temperature, load, volt{u2026}) without failure.The Reliability in the stress strength model describes the life of component which has a random strength X due to random stress Y. Stress and strength is described by the probability density functions. However, component strength may change from component to component because of variations in the material properties due to variation in the production. The probability R1= P(Y<X ), plays an important role in reliability analysis as it represent reliability in a stress-strength model and availability when Y and X are stress and strength variables, respectively follow up one of distribution such as stress Y is smallest than strength X. Furthermore the probability R2=P (Y<X<Z) represents reliability in a stress-strength model and availability when Y, Z and X are stress and strength variables, respectively such as strength X is greater than stress Y and smallest than stress Z. The inverse Rayleigh distribution is one of an important lifetime distribution in survival analysis that has many applications in the area of reliability studies. Estimation of stress strength reliability for inverse Rayleigh distribution in the presence of outlier can be obtained with a lot of method ,such that, moment estimation, maximum likelihood estimation and mixture estimation

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