lambdaAlgo {gmm4} | R Documentation |
The algorithms finds the vector or Lagrange multipliers that maximizes the GEL objective function for a given vector of coefficient θ.
Wu_lam(gmat, tol=1e-8, maxiter=50, k=1) EEL_lam(gmat, k=1) REEL_lam(gmat, tol=NULL, maxiter=50, k=1) ETXX_lam(gmat, lambda0, k, gelType, algo, method, control) getLambda(gmat, lambda0=NULL, gelType=NULL, rhoFct=NULL, tol = 1e-07, maxiter = 100, k = 1, method="BFGS", algo = c("nlminb", "optim", "Wu"), control = list())
gmat |
The n \times q matrix of moments |
lambda0 |
The q \times 1 vector of starting values for the Lagrange multipliers. |
tol |
A tolerance level for the stopping rule in the Wu algorithm |
maxiter |
The maximum number of iteration in the Wu algorithm |
gelType |
A character string specifying the type of GEL. The
available types are |
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 |
k |
A numeric scaling factor that is required when |
method |
This is the method for |
algo |
Which algorithm should be used to maximize the GEL objective
function. If set to |
control |
The ETXX_lam
is used for ETEL and ETHD. In general, it
computes lambda using ET, and returns the value of the objective
function determined by the gelType
.
It returns the vector ρ(gmat λ) when derive=0
,
ρ'(gmat λ) when derive=1
and ρ''(gmat
λ) when derive=2
.
Anatolyev, S. (2005), GMM, GEL, Serial Correlation, and Asymptotic Bias. Econometrica, 73, 983-1002.
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. (2011), GEL Criteria for Moment Condition Models. Econometric Theory, 27(6), 1192–1235.
Wu, C. (2005), Algorithms and R codes for the pseudo empirical likelihood method in survey sampling. Survey Methodology, 31(2), page 239.