Joint Quantile Regression through Bayesian Semiparametrics ...
We introduce a Bayesian semiparametric methodology for joint quantile regression with linearity and piecewise linearity constraints. We develop a probability model for all quantile curves in a continuum that define a coherent sampling distribution of the response variable. We provide a detailed illu...
| Main Authors: | , |
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| Format: | Other Non-Article Part of Journal/Newspaper |
| Language: | unknown |
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Carnegie Mellon University
2004
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.1184/r1/6586691.v1 https://kilthub.cmu.edu/articles/Joint_Quantile_Regression_through_Bayesian_Semiparametrics/6586691/1 |
| Summary: | We introduce a Bayesian semiparametric methodology for joint quantile regression with linearity and piecewise linearity constraints. We develop a probability model for all quantile curves in a continuum that define a coherent sampling distribution of the response variable. We provide a detailed illustration of model fitting and inference by analyzing wind speed trends of tropical cyclones in the North Atlantic. ... |
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