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simplexgof  

Bootstrap-Calibrated Goodness-of-Fit Test for Simplex Regression
View on CRAN: Click here


Download and install simplexgof package within the R console
Install from CRAN:
install.packages("simplexgof")

Install from Github:
library("remotes")
install_github("cran/simplexgof")

Install by package version:
library("remotes")
install_version("simplexgof", "0.1.0")



Attach the package and use:
library("simplexgof")
Maintained by
Raydonal Ospina
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-19
Latest Update: 2026-06-19
Description:
Implements the bootstrap-calibrated local-influence goodness-of-fit test for simplex regression models with constant or varying dispersion, following the local influence approach of Zhu and Zhang (2004) <doi:10.1093/biomet/91.3.579> and the simplex regression model of Barndorff-Nielsen and Jorgensen (1991) <doi:10.1016/0047-259X(91)90008-P>. The test statistic aggregates individual local-influence measures under case-weight perturbation. Because the first-order asymptotic normal calibration is severely liberal in finite samples, a parametric bootstrap calibration is provided that restores accurate size control and delivers high power against omitted covariates, neglected dispersion, and distributional misspecification. Plotting functions reproduce the figures and tables of the companion methodological paper. Computational kernels are implemented in 'C++' via 'Rcpp' and 'RcppArmadillo' for speed, and two real datasets are bundled.
How to cite:
Raydonal Ospina (2026). simplexgof: Bootstrap-Calibrated Goodness-of-Fit Test for Simplex Regression. R package version 0.1.0, https://cran.r-project.org/web/packages/simplexgof. Accessed 29 Oct. 2026.
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