LinearRegressionMDE
Minimum Distance Estimation in Linear Regression Model
Consider linear regression model Y = Xb + error where the distribution function of errors is unknown, but errors are independent and symmetrically distributed. The package contains a function named LRMDE which takes Y and X as input and returns minimum distance estimator of parameter b in the model.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0 |
rolling linux/jammy R-4.5 | LinearRegressionMDE_1.0.tar.gz |
19.8 KiB |
1.0 |
rolling linux/noble R-4.5 | LinearRegressionMDE_1.0.tar.gz |
19.8 KiB |
1.0 |
rolling source/ R- | LinearRegressionMDE_1.0.tar.gz |
9.3 KiB |
1.0 |
latest linux/jammy R-4.5 | LinearRegressionMDE_1.0.tar.gz |
19.8 KiB |
1.0 |
latest linux/noble R-4.5 | LinearRegressionMDE_1.0.tar.gz |
19.8 KiB |
1.0 |
latest source/ R- | LinearRegressionMDE_1.0.tar.gz |
9.3 KiB |
1.0 |
2026-04-26 source/ R- | LinearRegressionMDE_1.0.tar.gz |
9.3 KiB |
1.0 |
2026-04-23 source/ R- | LinearRegressionMDE_1.0.tar.gz |
9.3 KiB |
1.0 |
2026-04-09 windows/windows R-4.5 | LinearRegressionMDE_1.0.zip |
22.2 KiB |
1.0 |
2025-04-20 source/ R- | LinearRegressionMDE_1.0.tar.gz |
9.3 KiB |