Multicore Multivariable Isotonic Regression
Description
The goal of 'McMiso' is to provide functions for isotonic regression when there are multiple independent
variables. The functions solve the optimization problem using recursion and leverage parallel computing to improve
speed, and are useful for situations with relatively large number of covariates. The estimation method follows the
projective Bayes solution described in Cheung and Diaz (2023) .