rpc
Ridge Partial Correlation
Computes the ridge partial correlation coefficients in a high or ultra-high dimensional linear regression problem. An extended Bayesian information criterion is also implemented for variable selection. Users provide the matrix of covariates as a usual dense matrix or a sparse matrix stored in a compressed sparse column format. Detail of the method is given in the manual.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.0.3 |
rolling linux/jammy R-4.5 | rpc_2.0.3.tar.gz |
75.1 KiB |
2.0.3 |
rolling linux/noble R-4.5 | rpc_2.0.3.tar.gz |
77.1 KiB |
2.0.3 |
rolling source/ R- | rpc_2.0.3.tar.gz |
11.8 KiB |
2.0.3 |
latest linux/jammy R-4.5 | rpc_2.0.3.tar.gz |
75.1 KiB |
2.0.3 |
latest linux/noble R-4.5 | rpc_2.0.3.tar.gz |
77.1 KiB |
2.0.3 |
latest source/ R- | rpc_2.0.3.tar.gz |
11.8 KiB |
2.0.3 |
2026-04-26 source/ R- | rpc_2.0.3.tar.gz |
11.8 KiB |
2.0.3 |
2026-04-23 source/ R- | rpc_2.0.3.tar.gz |
11.8 KiB |
2.0.3 |
2026-04-09 windows/windows R-4.5 | rpc_2.0.3.zip |
491.3 KiB |
2.0.3 |
2025-04-20 source/ R- | rpc_2.0.3.tar.gz |
11.8 KiB |