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Estimation of Pareto Survival Function in the Presence of Outlying Observations
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E. S. Jeevanand
Published/Copyright:
March 10, 2010
Abstract
In the present paper we discuss the problem of estimating the survival function R(x) = P(X > x) of the Pareto distribution, when the sample contains discordant observations. Bayes point estimates and credible intervals are obtained by assuming exchangeable and identifiable models and by discarding the outlying observations under a class of loss functions. We illustrate the estimators with a real data-set and then compare the three estimators using a simulation study.
Published Online: 2010-03-10
Published in Print: 2006-October
© Heldermann Verlag
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- A Note on Nature and Significance of Stochastic Models
- Estimation of Pareto Survival Function in the Presence of Outlying Observations
- Loss Reduction in Point Estimation Problems
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Keywords for this article
Bayes estimator;
Pareto distribution;
survival function;
symmetric loss function
Articles in the same Issue
- A Note on Run Length Variability Reduction for EWMA Charting
- A Note on Nature and Significance of Stochastic Models
- Estimation of Pareto Survival Function in the Presence of Outlying Observations
- Loss Reduction in Point Estimation Problems
- Application of Arithmetic-Geometric Mean Inequality for Construction of Reliability Test Plan for Parallel Systems in the Presence of Covariates
- On Bayesian Estimation in a Parallel System
- Approximating Reliability of a System with Doubly Bounded Performance Functions
- Probability Weighted Moments Approach to Quality Control Charts
- Weibull Extension of Bivariate Exponential Regression Model with Gamma Frailty for Survival Data
- Nonlinear Tobit Decomposition
- Reliability Test Plans for Exponentiated Log-Logistic Distribution
- Transient Analysis of a System with Queue Dependent Servers and Controllable Arrivals
