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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.
| Version: | 1.0 |
| Depends: | R (≥ 3.2.2) |
| Published: | 2015-09-14 |
| Author: | Jiwoong Kim [aut, cre] |
| Maintainer: | Jiwoong Kim <kimjiwo2 at stt.msu.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | LinearRegressionMDE results |
| Reference manual: | LinearRegressionMDE.pdf |
| Package source: | LinearRegressionMDE_1.0.tar.gz |
| Windows binaries: | r-devel: LinearRegressionMDE_1.0.zip, r-release: LinearRegressionMDE_1.0.zip, r-oldrel: LinearRegressionMDE_1.0.zip |
| macOS binaries: | r-release (arm64): LinearRegressionMDE_1.0.tgz, r-oldrel (arm64): LinearRegressionMDE_1.0.tgz, r-release (x86_64): LinearRegressionMDE_1.0.tgz, r-oldrel (x86_64): LinearRegressionMDE_1.0.tgz |
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