Description Usage Arguments Value References See Also Examples
The main functions and methods to fit any model with GEL. 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.
1 2 3 4 5 6 7 8 9  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"),
lControl=list(), tControl=list())

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 (see detailsbelow). 
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, a formula or a list of formulas. For
these cases, they are needed to create the 
lambda0 
The q \times 1 vector of starting values for the Lagrange multipliers. By default a zero vector is used. 
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 G(θ,x) which returns a q\times k matrix of derivatives of \bar{g}(θ) with respect to θ. 
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 ρ(v). This is
for users who want a GEL model that is not built in the package. The
four arguments of the function must be 
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. 
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. 
It returns an object of class "gelfit"
Anatolyev, S. (2005), GMM, GEL, Serial Correlation, and Asymptotic Bias. Econometrica, 73, 9831002.
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, 20842102.
Kitamura, Y. and Otsu, T. and Evdokimov, K. (2013), Robustness, Infinitesimal Neighborhoods and Moment Restrictions. Econometrica, 81, 11851201.
Newey, W.K. and Smith, R.J. (2004), Higher Order Properties of GMM and Generalized Empirical Likelihood Estimators. Econometrica, 72, 219255.
Smith, R.J. (2004), GEL Criteria for Moment Condition Models. Working paper, CEMMAP.
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