Pages that link to "Item:Q2863066"
From MaRDI portal
The following pages link to Reliability estimation in stress–strength models: an MCMC approach (Q2863066):
Displaying 16 items.
- Bayesian and classical estimation of stress-strength reliability for inverse Weibull lifetime models (Q1662759) (← links)
- Reliability estimation of stress-strength model using finite mixture distributions under progressively interval censoring (Q1757393) (← links)
- Bayesian estimation of system reliability in Brownian stress-strength models (Q1881375) (← links)
- Estimation of reliability for multi-component stress-strength model based on modified Weibull distribution (Q2062411) (← links)
- Approximation of continuous random variables for the evaluation of the reliability parameter of complex stress-strength models (Q2171315) (← links)
- Bayes estimation of \(P(Y < X)\) for the Weibull distribution with arbitrary parameters (Q2290230) (← links)
- Inferences on Stress-Strength Reliability from Weighted Lindley Distributions (Q2796908) (← links)
- On estimation of stress–strength parameter using record values from proportional hazard rate models (Q2830791) (← links)
- Inferences on stress–strength reliability based on ranked set sampling data in case of Lindley distribution (Q4960737) (← links)
- Prediction under an adaptive progressive type-II censoring scheme for Burr Type-XII distribution (Q5079807) (← links)
- Estimation of generalized exponential distribution based on an adaptive progressively type-II censored sample (Q5106854) (← links)
- Reliability analysis of Birnbaum–Saunders model based on progressive type-II censoring (Q5107334) (← links)
- Reliability estimation in multicomponent stress–strength model for Topp-Leone distribution (Q5107500) (← links)
- (Q5154551) (← links)
- Statistical inferences for stress–strength in the proportional hazard models based on progressive Type-II censored samples (Q5220728) (← links)
- Bayesian inference for multicomponent stress-strength model under Weibull distribution (Q6559915) (← links)