McMiso
Multicore Multivariable Isotonic Regression
Provides functions for isotonic regression and classification when there are multiple independent variables. The functions solve the optimization problem using a projective Bayes approach with recursive sequential update algorithms, and are useful for situations with a relatively large number of covariates. Supports binary outcomes via a Beta-Binomial conjugate model ('miso', 'PBclassifier') and continuous outcomes via a Normal-Inverse-Chi-Squared conjugate model ('misoN'). Parallel computing wrappers ('mcmiso', 'mcPBclassifier', 'mcmisoN') are provided that run the down-up and up-down algorithms simultaneously and return whichever finishes first. The estimation method follows the projective Bayes solution described in Cheung and Diaz (2023) <doi:10.1093/jrsssb/qkad014>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.0 |
rolling linux/jammy R-4.5 | McMiso_0.2.0.tar.gz |
115.7 KiB |
0.2.0 |
rolling linux/noble R-4.5 | McMiso_0.2.0.tar.gz |
115.6 KiB |
0.2.0 |
rolling source/ R- | McMiso_0.2.0.tar.gz |
15.9 KiB |
0.2.0 |
latest linux/jammy R-4.5 | McMiso_0.2.0.tar.gz |
115.7 KiB |
0.2.0 |
latest linux/noble R-4.5 | McMiso_0.2.0.tar.gz |
115.6 KiB |
0.2.0 |
latest source/ R- | McMiso_0.2.0.tar.gz |
15.9 KiB |
0.2.0 |
2026-04-26 source/ R- | McMiso_0.2.0.tar.gz |
15.9 KiB |
0.2.0 |
2026-04-23 source/ R- | McMiso_0.2.0.tar.gz |
15.9 KiB |
0.2.0 |
2026-04-09 windows/windows R-4.5 | McMiso_0.2.0.zip |
117.9 KiB |