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