kcmeans
Conditional Expectation Function Estimation with K-Conditional-Means
Implementation of the KCMeans regression estimator studied by Wiemann (2023) <arXiv:2311.17021> for expectation function estimation conditional on categorical variables. Computation leverages the unconditional KMeans implementation in one dimension using dynamic programming algorithm of Wang and Song (2011) <doi:10.32614/RJ-2011-015>, allowing for global solutions in time polynomial in the number of observed categories.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | kcmeans_0.1.0.tar.gz |
25.3 KiB |
0.1.0 |
rolling linux/noble R-4.5 | kcmeans_0.1.0.tar.gz |
25.2 KiB |
0.1.0 |
rolling source/ R- | kcmeans_0.1.0.tar.gz |
12.7 KiB |
0.1.0 |
latest linux/jammy R-4.5 | kcmeans_0.1.0.tar.gz |
25.3 KiB |
0.1.0 |
latest linux/noble R-4.5 | kcmeans_0.1.0.tar.gz |
25.2 KiB |
0.1.0 |
latest source/ R- | kcmeans_0.1.0.tar.gz |
12.7 KiB |
0.1.0 |
2026-04-26 source/ R- | kcmeans_0.1.0.tar.gz |
12.7 KiB |
0.1.0 |
2026-04-23 source/ R- | kcmeans_0.1.0.tar.gz |
12.7 KiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | kcmeans_0.1.0.zip |
29.4 KiB |
0.1.0 |
2025-04-20 source/ R- | kcmeans_0.1.0.tar.gz |
12.7 KiB |