diff --git a/R/iterative.GMM.R b/R/iterative.GMM.R
index 7b02b0d..8774529 100644
--- a/R/iterative.GMM.R
+++ b/R/iterative.GMM.R
@@ -10,23 +10,20 @@
 #' @param start Starting values for the parameters and lagrangian
 #' @param conditions.vector Vector of moment conditions
 #' @param data Individual data sample
-#' @param ... Functions of the vector of moment conditions
 #' @param W Weighting matrix
-#' @param R Linear constraint matrix of coefficients
-#' @param r Linear constraint constants
+#' @param ... Functions of the vector of moment conditions
 #' @param max.iter Maximum number of iterations
 #' @param epsilon Minimum precision level
 #' @return A list containing the optimized vector of parameter and corresponding covariance matrix
 #' @export iterative.GMM
 #' @author François Pelletier
-iterative.GMM <- function(start,conditions.vector,data,...,
-		W=diag(length(conditions.vector)),R=0,r=0,lagrangian.start=rep(0,length(conditions.vector)),max.iter=50,epsilon=1E-6)
+iterative.GMM <- function(start,conditions.vector,data,W,...,max.iter=50,epsilon=1E-6)
 {
-	theta1 <- optim.GMM(start,conditions.vector,data,...,W,R,r,lagrangian.start)
+	theta1 <- optim.GMM(start,conditions.vector,data,W,...)
 	i <- 1
 	repeat
 	{
-		theta2 <- optim.GMM(theta1,conditions.vector,data,...,W,R,r,lagrangian.start)
+		theta2 <- optim.GMM(theta1,conditions.vector,data,W,...)
 		S <- covariance.GMM(conditions.vector,param,data,...)
 		if(sqrt(sum((theta1-theta2)^2))<epsilon)
 			return(list(par=theta2,cov=S))
diff --git a/R/mean.variance.gmm.vector.R b/R/mean.variance.gmm.vector.R
index 90b32ed..aa0b3cd 100644
--- a/R/mean.variance.gmm.vector.R
+++ b/R/mean.variance.gmm.vector.R
@@ -8,13 +8,13 @@
 
 #' GMM vector for mean and variance moment conditions
 #' @param param Estimated parameters
-#' @param X Data Sample
+#' @param data Data Sample
 #' @param meanf Mean function
 #' @param variancef Variance function
 #' @return A two column matrix of differences
 #' @export meanvariance.gmm.vector
 #' @author François Pelletier
-meanvariance.gmm.vector <- function(param,X,meanf,variancef)
+meanvariance.gmm.vector <- function(param,data,meanf,variancef)
 {
-	cbind(X-meanf(param),(X-meanf(param))^2 - variancef(param))
+	cbind(data-meanf(param),(data-meanf(param))^2 - variancef(param))
 }
diff --git a/R/objective.GMM.R b/R/objective.GMM.R
index ce00a1b..4786c67 100644
--- a/R/objective.GMM.R
+++ b/R/objective.GMM.R
@@ -9,8 +9,8 @@
 #' @param param Vector of parameters
 #' @param conditions.vector Vector of moment conditions
 #' @param data Individual data sample
-#' @param ... Functions of the vector of moment conditions
 #' @param W Weighting matrix
+#' @param ... Functions of the vector of moment conditions
 #' @return A scalar value
 #' @export objective.GMM
 #' @author François Pelletier
diff --git a/R/optim.GMM.R b/R/optim.GMM.R
index 77c57f9..af8c28a 100644
--- a/R/optim.GMM.R
+++ b/R/optim.GMM.R
@@ -10,8 +10,8 @@
 #' @param start Starting values for the parameters
 #' @param conditions.vector Vector of moment conditions
 #' @param data Individual data sample
-#' @param ... Functions of the vector of moment conditions
 #' @param W Weighting matrix
+#' @param ... Functions of the vector of moment conditions
 #' @return a list with optimization results
 #' @export optim.GMM
 #' @author François Pelletier
diff --git a/man/iterative.GMM.Rd b/man/iterative.GMM.Rd
index 312fd15..106facb 100644
--- a/man/iterative.GMM.Rd
+++ b/man/iterative.GMM.Rd
@@ -2,9 +2,7 @@
 \alias{iterative.GMM}
 \title{Iterative GMM method}
 \usage{
-iterative.GMM(start, conditions.vector, data, ...,
-  W = diag(length(conditions.vector)), R = 0, r = 0,
-  lagrangian.start = rep(0, length(conditions.vector)), max.iter = 50,
+iterative.GMM(start, conditions.vector, data, W, ..., max.iter = 50,
   epsilon = 1e-06)
 }
 \arguments{
@@ -15,13 +13,9 @@ iterative.GMM(start, conditions.vector, data, ...,
 
   \item{data}{Individual data sample}
 
-  \item{...}{Functions of the vector of moment conditions}
-
   \item{W}{Weighting matrix}
 
-  \item{R}{Linear constraint matrix of coefficients}
-
-  \item{r}{Linear constraint constants}
+  \item{...}{Functions of the vector of moment conditions}
 
   \item{max.iter}{Maximum number of iterations}
 
diff --git a/man/meanvariance.gmm.vector.Rd b/man/meanvariance.gmm.vector.Rd
index a90da73..288ba43 100644
--- a/man/meanvariance.gmm.vector.Rd
+++ b/man/meanvariance.gmm.vector.Rd
@@ -2,12 +2,12 @@
 \alias{meanvariance.gmm.vector}
 \title{GMM vector for mean and variance moment conditions}
 \usage{
-meanvariance.gmm.vector(param, X, meanf, variancef)
+meanvariance.gmm.vector(param, data, meanf, variancef)
 }
 \arguments{
   \item{param}{Estimated parameters}
 
-  \item{X}{Data Sample}
+  \item{data}{Data Sample}
 
   \item{meanf}{Mean function}
 
diff --git a/man/objective.GMM.Rd b/man/objective.GMM.Rd
index 345bd20..1d2e906 100644
--- a/man/objective.GMM.Rd
+++ b/man/objective.GMM.Rd
@@ -11,9 +11,9 @@ objective.GMM(param, conditions.vector, data, W, ...)
 
   \item{data}{Individual data sample}
 
-  \item{...}{Functions of the vector of moment conditions}
-
   \item{W}{Weighting matrix}
+
+  \item{...}{Functions of the vector of moment conditions}
 }
 \value{
 A scalar value
diff --git a/man/optim.GMM.Rd b/man/optim.GMM.Rd
index 5cb4204..dd5ddbf 100644
--- a/man/optim.GMM.Rd
+++ b/man/optim.GMM.Rd
@@ -11,9 +11,9 @@ optim.GMM(start, conditions.vector, data, W, ...)
 
   \item{data}{Individual data sample}
 
-  \item{...}{Functions of the vector of moment conditions}
-
   \item{W}{Weighting matrix}
+
+  \item{...}{Functions of the vector of moment conditions}
 }
 \value{
 a list with optimization results