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Yang, Dan; Small, Dylan S.

An R package and a study of methods for computing empirical likelihood. (English) Zbl 1431.62011

J. Stat. Comput. Simulation 83, No. 7, 1363-1372 (2013).
Summary: 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.

Cited in 3 Documents

MSC:

62-04 Software, source code, etc. for problems pertaining to statistics
62G05 Nonparametric estimation
62P20 Applications of statistics to economics

Keywords:

convex optimization; quasi-Newton method; instrumental variables; conjugate gradient method

Software:

el.convex; R; emplik
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\textit{D. Yang} and \textit{D. S. Small}, J. Stat. Comput. Simulation 83, No. 7, 1363--1372 (2013; Zbl 1431.62011)
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