Packaged: 2020-07-05 15:06:49 UTC; ramikrispin

Description: 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 (2020) <arXiv:2007.00830>
study the unmatched regression setting where the univariate regression function is known to
be monotone.     This package implements (two) gradient    descent method(s) to
compute the estimator developed in  Balabdaoui, Doss, and Durot (2020).
Author: Charles Doss [aut, cre] (<https://orcid.org/0000-0003-1364-5222>)

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.

Title: Unification of Clustering Results from Multiple Datasets using
Description: Consensus clustering by the unification of clustering results from multiple datasets using external specifications.

Title: Tools for creating universal numeric fingerprints for data.
Description:  Computes a univeral numeric fingerprint of the data.
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