Abstract
Quantile regressions have been invented centuries ago but have been virtually unused due to computational complexity. Thanks to computers and modern statistical software computations have become easy today. The principle of regression is, that the best fit mathematical model is chosen for a dataset, and, then, it is tested how far distant from this model the data are. Quantile regression is like traditional linear regression, but instead of using a regression coefficient based on means
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Cleophas, T.J., Zwinderman, A.H. (2021). General Introduction. In: Quantile Regression in Clinical Research . Springer, Cham. https://doi.org/10.1007/978-3-030-82840-0_1
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DOI: https://doi.org/10.1007/978-3-030-82840-0_1
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