A Corrected Plug-in Method for Quantile Interval Construction through a Transformed Regression
We propose a corrected plug-in method for constructing confidence intervals of the conditional quantiles of an original response variable through a transformed regression with heteroscedastic errors. The interval is easy to compute. Factors affecting the magnitude of the correction are examined anal...
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| المؤلفون الرئيسيون: | , |
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| التنسيق: | text |
| اللغة: | English |
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Institutional Knowledge at Singapore Management University
2007
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://ink.library.smu.edu.sg/soe_research/352 https://ink.library.smu.edu.sg/context/soe_research/article/1351/viewcontent/YangTse_JBES2007at.pdf |
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| المؤسسة: | Singapore Management University |
| اللغة: | English |
| الملخص: | We propose a corrected plug-in method for constructing confidence intervals of the conditional quantiles of an original response variable through a transformed regression with heteroscedastic errors. The interval is easy to compute. Factors affecting the magnitude of the correction are examined analytically through the special case of Box-Cox regression. Monte Carlo simulations show that the new method works well in general and is superior over the commonly used delta method and the quantile regression method. An empirical application is presented. [PUBLICATION ABSTRACT] |
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