39 lines
1.2 KiB
R
39 lines
1.2 KiB
R
# Iterative GMM method
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#
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# Author: Francois Pelletier
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#
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# LGPL-3.0
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###############################################################################
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#' Iterative GMM method
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#'
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#' @param start.value Starting values for the parameters and lagrangian
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#' @param conditions.vector Vector of moment conditions
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#' @param data Individual data sample
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#' @param W Weighting matrix
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#' @param ... Functions of the vector of moment conditions
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#' @param max.iter Maximum number of iterations
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#' @param epsilon Minimum precision level
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#' @return A list containing the optimized vector of parameter and corresponding covariance matrix
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#' @export iterative.GMM
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#' @author François Pelletier
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iterative.GMM <- function(start.value,conditions.vector,data,W,...,max.iter=50,epsilon=1E-6)
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{
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theta1 <- optim.GMM(start.value,conditions.vector=conditions.vector,data=data,W=W,...)$par
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i <- 1
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repeat
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{
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theta2 <- optim.GMM(theta1,conditions.vector,data,W,...)$par
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S <- covariance.GMM(theta2,conditions.vector,data,...)
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if(sqrt(sum((theta1-theta2)^2))<epsilon)
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return(list(par=theta2,cov=S))
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else if (i>max.iter)
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stop("Iterative GMM does not converge")
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else
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{
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theta1 <- theta2
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i <- i+1
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}
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}
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}
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