[Gmm-commits] r43 - in pkg/gmm: R man

[noreply at r-forge.r-project.org]

Author: chaussep
Date: 2011-11-30 16:59:56 +0100 (Wed, 30 Nov 2011)
New Revision: 43

Added:
   pkg/gmm/man/tsls.Rd
Modified:
   pkg/gmm/R/getModel.R
Log:
added manual for tsls and fixed getModel.baseGel

Modified: pkg/gmm/R/getModel.R
===================================================================
--- pkg/gmm/R/getModel.R	2011-11-29 22:02:25 UTC (rev 42)
+++ pkg/gmm/R/getModel.R	2011-11-30 15:59:56 UTC (rev 43)
@@ -150,6 +150,7 @@
     }	
   else
     {
+    x <- P$x
     clname <- paste(class(P), ".mod", sep = "")
     P$gform <- NULL
     if (!is.function(object$gradv))
@@ -163,7 +164,6 @@
       }
 
     }
-
   if (P$smooth)
     {
     if(P$kernel == "Truncated")

Added: pkg/gmm/man/tsls.Rd
===================================================================
--- pkg/gmm/man/tsls.Rd	                        (rev 0)
+++ pkg/gmm/man/tsls.Rd	2011-11-30 15:59:56 UTC (rev 43)
@@ -0,0 +1,86 @@
+\name{tsls}
+
+\alias{tsls}
+
+\title{Two stage least squares estimation}
+
+\description{
+ Function to estimate a linear model by the two stage least squares method.
+}
+\usage{
+tsls(g,x,data)
+}
+\arguments{
+\item{g}{A formula describing the linear regression model (see details below).}
+
+\item{x}{The matrix of instruments (see details below).}
+
+\item{data}{A data.frame or a matrix with column names (Optionnal). }
+}
+
+\details{
+The function just calls \code{\link{gmm}} with the option vcov="iid". It just simplifies the the implementation of 2SLS. The users don't have to worry about all the options offered in \code{\link{gmm}}. The model is 
+\deqn{
+Y_i = X_i\beta + u_i
+}
+In the first step, \code{\link{lm}}  is used to regress \eqn{X_i} on the set of instruments \eqn{Z_i}. The second step also uses \code{\link{lm}} to regress \eqn{Y_i} on the fitted values of the first step. 
+}
+
+\value{
+'tsls' returns an object of 'class' '"tsls"' which inherits from  class '"gmm"'.
+
+The functions 'summary' is used to obtain and print a summary of the results.  It also compute the J-test of overidentying restriction
+
+The object of class "gmm" is a list containing at least:
+
+\item{coefficients}{\eqn{k\times 1} vector of coefficients}
+
+\item{residuals}{the residuals, that is response minus fitted values if "g" is a formula.}
+
+\item{fitted.values}{the fitted mean values if "g" is a formula.}
+
+\item{vcov}{the covariance matrix of the coefficients}
+
+\item{objective}{the value of the objective function \eqn{\| var(\bar{g})^{-1/2}\bar{g}\|^2}}
+
+\item{terms}{the \code{\link{terms}} object used when g is a formula.}
+
+\item{call}{the matched call.}
+ 
+\item{y}{if requested, the response used (if "g" is a formula).}
+
+\item{x}{if requested, the model matrix used if "g" is a formula or the data if "g" is a function.}
+
+\item{model}{if requested (the default), the model frame used if "g" is a formula.}
+
+\item{algoInfo}{Information produced by either \code{\link{optim}} or \code{\link{nlminb}} related to the convergence if "g" is a function. It is printed by the \code{summary.gmm} method.}
+}
+
+
+\references{
+
+  Hansen, L.P. (1982),
+  Large Sample Properties of Generalized Method of Moments Estimators.
+  \emph{Econometrica}, \bold{50},
+  1029-1054,
+
+}
+\examples{
+
+n <- 1000
+e <- arima.sim(n,model=list(ma=.9))
+C <- runif(n,0,5)
+Y <- rep(0,n)
+Y[1] = 1 + 2*C[1] + e[1]
+for (i in 2:n){
+Y[i] = 1 + 2*C[i] + 0.9*Y[i-1] + e[i]
+}
+Yt <- Y[5:n]
+X <- cbind(C[5:n],Y[4:(n-1)])
+Z <- cbind(C[5:n],Y[3:(n-2)],Y[2:(n-3)],Y[1:(n-4)]) 
+
+res <- tsls(Yt~X,~Z)
+res
+
+}
+