Performs multiple empirical likelihood tests. It offers an easy-to-use interface and flexibility in specifying hypotheses and calibration methods, extending the framework to simultaneous inferences. The core computational routines are implemented using the 'Eigen' 'C++' library and 'RcppEigen' interface, with 'OpenMP' for parallel computation. Details of the testing procedures are provided in Kim, MacEachern, and Peruggia (2023) doi:10.1080/10485252.2023.2206919 . A companion paper by Kim, MacEachern, and Peruggia (2024) doi:10.18637/jss.v108.i05 is available for further information. This work was supported by the U.S. National Science Foundation under Grants No. SES-1921523 and DMS-2015552.
References
Kim E, MacEachern SN, Peruggia M (2023). “Empirical likelihood for the analysis of experimental designs.” Journal of Nonparametric Statistics, 35(4), 709–732. doi:10.1080/10485252.2023.2206919 .
Kim E, MacEachern SN, Peruggia M (2024). “melt: Multiple Empirical Likelihood Tests in R.” Journal of Statistical Software, 108(5), 1–33. doi:10.18637/jss.v108.i05 .
Author
Maintainer: Eunseop Kim markean@pm.me [copyright holder]
Other contributors:
Steven MacEachern [contributor, thesis advisor]
Mario Peruggia [contributor, thesis advisor]
Pierre Chausse [reviewer]
Alex Stringer [reviewer]