Package: KoulMde
Title: Koul's Minimum Distance Estimation in Linear Regression and
        Autoregression Model
Version: 1.0
Authors@R: person("Jiwoong", "Kim", email = "kimjiwo2@stt.msu.edu", role = c("aut", "cre"))
Description: Consider linear regression model and autoregressive model of order p where errors in the linear regression model and innovations in the autoregression model are independent and symmetrically distributed. Hira L. Koul proposed a nonparametric minimum distance estimation method by minimizing L2-type distance between certain weighted residual empirical distribution functions. He also proposed a simpler version of  the loss function by using symmetry of the integrating measure in the distance. This package contains two functions: KoulLrMde() and KoulArMde(). KoulLrMde() and KoulArMde() provide minimum distance estimators for linear regression model and autoregression model, respectively, where both are based on Koul's method. These two functions take much less time for the computation than those based on parametric minimum distance estimation methods. 
Depends: R (>= 3.2.2)
License: GPL-2
LazyData: true
NeedsCompilation: no
Packaged: 2015-09-25 16:35:44 UTC; Jason
Author: Jiwoong Kim [aut, cre]
Maintainer: Jiwoong Kim <kimjiwo2@stt.msu.edu>
Repository: CRAN
Date/Publication: 2015-09-25 20:33:27
