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Semi-Parametric Estimation of PX,Y (X > Y)
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E. S. Jeevanand
Veröffentlicht/Copyright:
15. März 2010
Abstract
In the context of reliability the stress-strength model describes the life of a component which has a random strength X and is subject to a stress Y. The component fails at the instant the stress applied to it exceeds the strength and the component will work satisfactory in case of the event {(x, y) | x > y}. Thus R = PX,Y ({(x, y) | x > y}) is a measure of system reliability. In this paper, we obtain semi parametric estimators of the reliability under stress-strength model for the exponential distribution under complete and censored samples. We illustrate the performance of the estimators using a simulation study.
Published Online: 2010-03-15
Published in Print: 2008-October
© Heldermann Verlag
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Artikel in diesem Heft
- Stochastic Measurement Procedures Based on Stationary Time Series
- Semi-Parametric Estimation of PX,Y (X > Y)
- On The Performance of A New Test of Exponentiality Against IFR Alternatives Based on the L-statistic Approach
- Control Chart for Autocorrelated Processes with Heavy Tailed Distributions
- Designing the Scale Counting Procedure for Large Numbers of Small Parts
- MTBF for K-out-of-N: G Systems with M Failure Modes
- Non-parametric Control Chart for Controlling Variability Based on Rank Test
- Bounds for Distorted Risk Measures
- Parameter Estimation for the Bivariate Exponential Distribution by the EM Algorithm Based on Censored Samples
- Explicit Expressions for Moments of Log Normal Order Statistics
- Partially Specified Prior
- The Need for a Standard for Making Predictions
Schlagwörter für diesen Artikel
Exponential distribution;
Reliability;
Censored sample;
Semi parametric estimates
Artikel in diesem Heft
- Stochastic Measurement Procedures Based on Stationary Time Series
- Semi-Parametric Estimation of PX,Y (X > Y)
- On The Performance of A New Test of Exponentiality Against IFR Alternatives Based on the L-statistic Approach
- Control Chart for Autocorrelated Processes with Heavy Tailed Distributions
- Designing the Scale Counting Procedure for Large Numbers of Small Parts
- MTBF for K-out-of-N: G Systems with M Failure Modes
- Non-parametric Control Chart for Controlling Variability Based on Rank Test
- Bounds for Distorted Risk Measures
- Parameter Estimation for the Bivariate Exponential Distribution by the EM Algorithm Based on Censored Samples
- Explicit Expressions for Moments of Log Normal Order Statistics
- Partially Specified Prior
- The Need for a Standard for Making Predictions
