| 1. | Quantile regression is desired if conditional quantile functions are of interest.
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| 2. | Quantile regression is desired if conditional quantile functions are of interest.
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| 3. | However, the main attraction of quantile regression goes beyond that.
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| 4. | It is the reciprocal of the pdf composed with the quantile function.
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| 5. | Statistical applications of quantile functions are discussed extensively by Gilchrist.
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| 6. | Thus the 90 % quantile is exactly 4 " 3 / 5.
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| 7. | Koenker is mostly known for his contributions to quantile regression.
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| 8. | Quantile normalization is frequently used in microarray data analysis.
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| 9. | #Continuous probability distribution, with finite support, and closed-form quantile function
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| 10. | The cumulative distribution function is computed by numerically inverting the quantile function given above.
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