Package: KoulMde
Title: Koul's Minimum Distance Estimation in Linear Regression and
        Autoregression Model by Coordinate Descent Algorithm
Version: 2.2.0
Authors@R: person("Jiwoong", "Kim", email = "kimjiwo2@stt.msu.edu", role = c("aut", "cre"))
Description: Consider linear regression model and autoregressive model of
    order q where errors in the linear regression model and innovations in the
    autoregression model are independent and symmetrically distributed. Hira L.
    Koul (1986) <DOI:10.1214/aos/1176350059> proposed a nonparametric minimum 
    distance estimation method by minimizing L2-type distance between certain 
    weighted residual empirical processes. He also proposed a simpler version of 
    the loss function by using symmetry of the integrating measure in the distance. 
    This package contains three functions: KoulLrMde(), KoulArMde(), and Koul2StageMde(). 
    The former two 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. Koul2StageMde() provides estimators for regression
    and autoregressive coefficients of linear regression model with autoregressive
    errors through minimum distant method of two stages.
Depends: R (>= 3.2.2)
License: GPL-2
LazyData: true
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-11-10 01:50:54 UTC; jkim66
Author: Jiwoong Kim [aut, cre]
Maintainer: Jiwoong Kim <kimjiwo2@stt.msu.edu>
Repository: CRAN
Date/Publication: 2016-11-10 13:16:52
