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.

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

Documentation:

Reference manual: LinearRegressionMDE.pdf

Downloads:

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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