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Quantile Surfaces – Generalizing Quantile Regression to Multivariate Targets
[article]
2020
arXiv
pre-print
In this article, we present a novel approach to multivariate probabilistic forecasting. Our approach is based on an extension of single-output quantile regression (QR) to multivariate-targets, called quantile surfaces (QS). QS uses a simple yet compelling idea of indexing observations of a probabilistic forecast through direction and vector length to estimate a central tendency. We extend the single-output QR technique to multivariate probabilistic targets. QS efficiently models dependencies in
arXiv:2010.05898v1
fatcat:hbtu4z725feuxldsqeije6wxtq