2021/06/29 by Anja Mühlemann, Johanna F. Ziegel, Mühlemann, Anja +1
Computer Science · Engineering · Mathematics · #Advanced Statistical Methods and Models #Computational Drug Discovery Methods #FOS: Mathematics #Process Optimization and Integration #Statistics Theory (math.ST) #math.ST #stat.TH
paper · pdf · doi:10.48550/arxiv.2106.15369
arxiv created 2021/06/29 · openalex publication_date 2021/06/29 · arxiv updated 2021/06/30 · openalex created_date 2021/07/05 · openalex updated_date 2026/07/28
We study the non-parametric isotonic regression problem for bivariate elicitable functionals that are given as an elicitable univariate functional and its Bayes risk. Prominent examples for functionals of this type are (mean, variance) and (Value-at-Risk, Expected Shortfall), where the latter pair consists of important risk measures in finance. We present our results for totally ordered covariates but extenstions to partial orders are given in the appendix.