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Statistical Inference on Residual LifeOther Methods for Inference on Quantiles

Statistical Inference on Residual Life: Other Methods for Inference on Quantiles [While the quantiles have many advantages including robustness, straightforward interpretation, and presentation of specific information, they also suffer from some pitfalls. First of all, evaluation of the variance formulas of the quantiles involves estimation of the probability density function under independent and/or dependent censoring. A method that was adopted to avoid this hurdle produced complicated variance formulas. Second, when the censoring proportion is high, higher quantiles cannot be defined. In this chapter, we review two recent approaches that address these issues; the empirical likelihood ratio-based method and a Bayesian method.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Statistical Inference on Residual LifeOther Methods for Inference on Quantiles

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Publisher
Springer New York
Copyright
© Springer Science+Business Media New York 2014
ISBN
978-1-4939-0004-6
Pages
119 –139
DOI
10.1007/978-1-4939-0005-3_5
Publisher site
See Chapter on Publisher Site

Abstract

[While the quantiles have many advantages including robustness, straightforward interpretation, and presentation of specific information, they also suffer from some pitfalls. First of all, evaluation of the variance formulas of the quantiles involves estimation of the probability density function under independent and/or dependent censoring. A method that was adopted to avoid this hurdle produced complicated variance formulas. Second, when the censoring proportion is high, higher quantiles cannot be defined. In this chapter, we review two recent approaches that address these issues; the empirical likelihood ratio-based method and a Bayesian method.]

Published: Dec 14, 2013

Keywords: Quantile Regression; Empirical Likelihood; Residual Life; Meier Estimator; Empirical Likelihood Method

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