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Correction iterative GMM

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This commit is contained in:
François Pelletier 2014-03-08 00:41:05 -05:00
parent 445e334b28
commit 3aecd56cc4
8 changed files with 17 additions and 26 deletions
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11
R/iterative.GMM.R
View file

@ -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))

6
R/mean.variance.gmm.vector.R
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@ -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))
}

2
R/objective.GMM.R
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@ -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

2
R/optim.GMM.R
View file

@ -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

10
man/iterative.GMM.Rd
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@ -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}

4
man/meanvariance.gmm.vector.Rd
View file

@ -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}

4
man/objective.GMM.Rd
View file

@ -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

4
man/optim.GMM.Rd
View file

@ -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