PerMat
Performance Metrics in Predictive Modeling
Performance metric provides different performance measures like mean squared error, root mean square error, mean absolute deviation, mean absolute percentage error etc. of a fitted model. These can provide a way for forecasters to quantitatively compare the performance of competing models. For method details see (i) Pankaj Das (2020) <http://krishi.icar.gov.in/jspui/handle/123456789/44138>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | PerMat_0.1.0.tar.gz |
31.5 KiB |
0.1.0 |
rolling linux/noble R-4.5 | PerMat_0.1.0.tar.gz |
31.6 KiB |
0.1.0 |
rolling source/ R- | PerMat_0.1.0.tar.gz |
13.3 KiB |
0.1.0 |
latest linux/jammy R-4.5 | PerMat_0.1.0.tar.gz |
31.5 KiB |
0.1.0 |
latest linux/noble R-4.5 | PerMat_0.1.0.tar.gz |
31.6 KiB |
0.1.0 |
latest source/ R- | PerMat_0.1.0.tar.gz |
13.3 KiB |
0.1.0 |
2026-04-26 source/ R- | PerMat_0.1.0.tar.gz |
13.3 KiB |
0.1.0 |
2026-04-23 source/ R- | PerMat_0.1.0.tar.gz |
13.3 KiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | PerMat_0.1.0.zip |
38.0 KiB |
0.1.0 |
2025-04-20 source/ R- | PerMat_0.1.0.tar.gz |
13.3 KiB |