| gel4 {momentfit} | R Documentation |
GEL estimation
Description
The main functions and methods to fit any model with GEL. As opposed to
gelFit, models don't need to be created. It is all done by
the functions. It is meant to be more user friendly.
Usage
gel4(g, x=NULL, theta0=NULL,lambda0=NULL, getVcov=FALSE,
gelType = c("EL","ET","EEL","HD", "REEL","ETEL","ETHD"),
vcov = c("MDS","iid","HAC"), grad=NULL,
vcovOptions=list(), centeredVcov = TRUE,
cstLHS=NULL, cstRHS=NULL, lamSlv=NULL,
rhoFct=NULL, initTheta=c("gmm", "theta0"),
data = parent.frame(),
coefSlv=c("optim","nlminb","constrOptim"),
smooth=FALSE,
lControl=list(), tControl=list())
Arguments
g |
A function of the form |
x |
The matrix or vector of data from which the function
|
theta0 |
A |
lambda0 |
The |
getVcov |
Should the method computes the covariance matrices of the coefficients and Lagrange multipliers. |
gelType |
A character string specifying the type of GEL. |
vcov |
Assumption on the properties of the moment conditions. |
grad |
A function of the form |
vcovOptions |
A list of options for the covariance matrix of the
moment conditions. See |
centeredVcov |
Should the moment function be centered when computing its covariance matrix. Doing so may improve inference. |
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 |
lamSlv |
An alternative solver for the Lagrange multiplier. By
default, either |
rhoFct |
An optional function that return |
initTheta |
Method to obtain the starting values for the
coefficient vector. By default the GMM estimate with identity matrix
is used. The second argument means that |
data |
A required data.frame, in which all variables in g and x can be found. |
smooth |
If TRUE, |
coefSlv |
Minimization solver for the coefficient vector. |
lControl |
A list of controls for the Lagrange multiplier algorithm. |
tControl |
A list of controls for the coefficient algorithm. |
Value
It returns an object of class "gelfit"
References
Anatolyev, S. (2005), GMM, GEL, Serial Correlation, and Asymptotic Bias. Econometrica, 73, 983-1002.
Andrews DWK (1991), Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation. Econometrica, 59, 817–858.
Kitamura, Yuichi (1997), Empirical Likelihood Methods With Weakly Dependent Processes. The Annals of Statistics, 25, 2084-2102.
Kitamura, Y. and Otsu, T. and Evdokimov, K. (2013), Robustness, Infinitesimal Neighborhoods and Moment Restrictions. Econometrica, 81, 1185-1201.
Newey, W.K. and Smith, R.J. (2004), Higher Order Properties of GMM and Generalized Empirical Likelihood Estimators. Econometrica, 72, 219-255.
Smith, R.J. (2004), GEL Criteria for Moment Condition Models. Working paper, CEMMAP.
See Also
Examples
data(simData)
res <- gel4(y~x1, ~z1+z2, vcov="MDS", gelType="ET", data=simData)
res