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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