The maximum empirical likelihood estimates for parameters defined by estimating equations.
theta
The value to be evaluated.
x
Data Matrix.
equation
The estimating equation by which the parameters are defined, must be put as a function of theta.
Value
The function returns a vector, with the same dimension as the mean, representing the prime image of the point theta, based on the similarity mapping defind in EEL calculation.
Details
The prime image was found by solving the equation $$f(\zeta'')=\zeta'.$$ See the reference paper for details.
References
Tsao, M. (2013). Extending the empirical likelihood by domain expansion. The Canadian Journal of Statistics, 41 (2), 257-274.
Tsao, M., & Wu, F. (2013). Empirical likelihood on the full parameter space. Annals of Statistics, 0 (00), 1-21. doi: 10.1214/13-AOS1143