An R package and a study of methods for computing empirical likelihood

Empirical likelihood (EL) is an important nonparametric statistical methodology. We develop a package in R called el.convex to implement EL for inference about a multivariate mean. This package contains five functions which use different optimization algorithms but meanwhile seek the same goal. These functions are based on the theory of convex optimization; they are Newton, Davidon-Fletcher-Powell, Broyden-Fletcher-Goldfarb-Shanno, conjugate gradient method, and damped Newton, respectively. We also compare them with the function el.test in the existing R package emplik, and discuss their relative advantages and disadvantages.