UMR: Unmatched Monotone Regression
Unmatched regression refers to the regression setting where
covariates and predictors are collected separately/independently and so are not paired together, as in the usual regression setting. Balabdaoui, Doss, and Durot (2021) <arXiv:2007.00830> study the unmatched regression setting where the univariate regression function is known to be monotone. This package implements methods for computing the estimator developed in Balabdaoui, Doss, and Durot (2021). The main method is an active-set-trust-region-based method.
||decon, trust, distr
||Charles Doss <cdoss at stat.umn.edu>
||GPL (≥ 3)
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