Description Usage Arguments Value References See Also Examples
The main functions and methods to fit any model with GMM. As opposed to
modelFit
, models don't need to be created. It is all done by
the functions. It is meant to be more user friendly. This document
needs to changed. It is just a copy and paste from the gmm package
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23  gmm4(g, x, theta0 = NULL, grad = NULL,
type = c("twostep", "iter", "cue", "onestep"),
vcov = c("iid", "HAC", "MDS", "TrueFixed", "CL"),
initW = c("ident", "tsls", "EbyE"), weights = "optimal",
itermaxit = 50, cstLHS=NULL, cstRHS=NULL,
vcovOptions=list(), survOptions=list(),
itertol = 1e07, centeredVcov = TRUE,
data = parent.frame(), ...)
## S4 method for signature 'formula'
tsls(model, x, vcov = c("iid", "HAC", "MDS", "CL"),
vcovOptions=list(), survOptions=list(), centeredVcov = TRUE,
data = parent.frame())
## S4 method for signature 'list'
tsls(model, x=NULL, vcov = c("iid", "HAC", "MDS",
"CL"), vcovOptions=list(), survOptions=list(),
centeredVcov = TRUE, data = parent.frame())
## S4 method for signature 'list'
ThreeSLS(model, x=NULL, vcov = c("iid", "HAC", "MDS",
"CL"), vcovOptions=list(), survOptions=list(),
centeredVcov = TRUE, data = parent.frame())

model 
A formula or a list of formulas. 
g 
A function of the form g(θ,x) and which returns a n \times q matrix with typical element g_i(θ,x_t) for i=1,...q and t=1,...,n. This matrix is then used to build the q sample moment conditions. It can also be a formula if the model is linear or nonlinear, or a list of formulas for systems of equations. 
x 
The matrix or vector of data from which the function g(θ,x) is computed. If "g" is a formula, it is an n \times Nh matrix of instruments or a formula (see details below). 
theta0 
A k \times 1 vector of starting values. It is required only when "g" is a function or a nonlinear equation defined by a formula, in which case, it must be a named vector 
grad 
A function of the form G(θ,x) which returns a
q\times k matrix of derivatives of \bar{g}(θ) with
respect to θ. By default, the numerical algorithm

type 
What GMM methods should we use? for

vcov 
Assumption on the properties of the random vector x. By
default, x is a weakly dependant process. The "iid" option will avoid
using the HAC matrix which will accelerate the estimation if one is
ready to make that assumption. The option "TrueFixed" is used only
when the matrix of weights is provided and it is the optimal one. For
type 
initW 
How should be compute the initial coefficient vector in the first. It only makes a difference for linear models for which the choice is GMM with identity matrix or twostage least quares. 
weights 
What weighting matrix to use? The
choices are 
itermaxit 
Maximum iterations for iterative GMM 
itertol 
Tolance for the stopping rule in iterative GMM 
centeredVcov 
Should the moment function be centered when computing its covariance matrix. Doing so may improve inference. 
data 
A data.frame or a matrix with column names (Optional). 
cstLHS 
The left hand side of the constraints to impose on the
coefficients. See 
cstRHS 
The right hand side of the constraints to impose on the
coefficients. See 
vcovOptions 
A list of options for the covariance matrix of the
moment conditions. See 
survOptions 
If needed, a list with the type of survey weights and
the weights as a numeric vector, data.frame or formula. The type is either

... 
Arguments to pass to 
It returns an object of class "gmmfit"
Zeileis A (2006), Objectoriented Computation of Sandwich Estimators. Journal of Statistical Software, 16(9), 1–16. URL http://www.jstatsoft.org/v16/i09/.
Andrews DWK (1991), Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation. Econometrica, 59, 817–858.
Newey WK & West KD (1987), A Simple, Positive SemiDefinite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix. Econometrica, 55, 703–708.
Newey WK & West KD (1994), Automatic Lag Selection in Covariance Matrix Estimation. Review of Economic Studies, 61, 631653.
Hansen, L.P. (1982), Large Sample Properties of Generalized Method of Moments Estimators. Econometrica, 50, 10291054,
Hansen, L.P. and Heaton, J. and Yaron, A.(1996), FiniteSample Properties of Some Alternative GMM Estimators. Journal of Business and Economic Statistics, 14 262280.
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