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  "Description": "Implements the bootstrap-calibrated local-influence\ngoodness-of-fit test for simplex regression models with\nconstant or varying dispersion, following the local influence\napproach of Zhu and Zhang (2004) <doi:10.1093/biomet/91.3.579>\nand the simplex regression model of Barndorff-Nielsen and\nJorgensen (1991) <doi:10.1016/0047-259X(91)90008-P>. The test\nstatistic aggregates individual local-influence measures under\ncase-weight perturbation. Because the first-order asymptotic\nnormal calibration is severely liberal in finite samples, a\nparametric bootstrap calibration is provided that restores\naccurate size control and delivers high power against omitted\ncovariates, neglected dispersion, and distributional\nmisspecification. Plotting functions reproduce the figures and\ntables of the companion methodological paper. Computational\nkernels are implemented in 'C++' via 'Rcpp' and 'RcppArmadillo'\nfor speed, and two real datasets are bundled.",
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