PLFD
Portmanteau Local Feature Discrimination for Matrix-Variate Data
The portmanteau local feature discriminant approach first identifies the local discriminant features and their differential structures, then constructs the discriminant rule by pooling the identified local features together. This method is applicable to high-dimensional matrix-variate data. See the paper by Xu, Luo and Chen (2023, <doi:10.1007/s13171-021-00255-2>).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.1 |
rolling linux/jammy R-4.5 | PLFD_0.2.1.tar.gz |
90.3 KiB |
0.2.1 |
rolling linux/noble R-4.5 | PLFD_0.2.1.tar.gz |
95.3 KiB |
0.2.1 |
rolling source/ R- | PLFD_0.2.1.tar.gz |
23.3 KiB |
0.2.1 |
latest linux/jammy R-4.5 | PLFD_0.2.1.tar.gz |
90.3 KiB |
0.2.1 |
latest linux/noble R-4.5 | PLFD_0.2.1.tar.gz |
95.3 KiB |
0.2.1 |
latest source/ R- | PLFD_0.2.1.tar.gz |
23.3 KiB |
0.2.1 |
2026-04-26 source/ R- | PLFD_0.2.1.tar.gz |
23.3 KiB |
0.2.1 |
2026-04-23 source/ R- | PLFD_0.2.1.tar.gz |
23.3 KiB |
0.2.1 |
2026-04-09 windows/windows R-4.5 | PLFD_0.2.1.zip |
503.0 KiB |
0.2.0 |
2025-04-20 source/ R- | PLFD_0.2.0.tar.gz |
127.2 KiB |