Wish List

Here are some to-dos for concurve in the future.

• More unit tests for various purposes as Alex Hayes describes in his wonderful article. He classifies them into three types, which I copy and paste below:
  • “Correctness tests check whether the code calculates the quantity it is supposed to calculated.”
  • “Parameter recovery tests check whether the implementation can recover correct parameters in well understood scenarios.”
  • “Convergence tests check whether iterative fitting procedures have actually reached a solution.”
  • “Identification tests check whether the solution is unique, and stable under small perturbations to the data.” * * *
• Make curve_rev() more usable for a wide range of scenarios (beyond proportions, and normal approximations). The confidence functions they produce especially break down with continuous variables, so I have completely disabled the option for now, and will implement an approach by working backwards from the deviance and log-likelihood functions. * * *
• Produce consonance/confidence functions for quantile regressions from the quantreg package
• Implementation with the nlme package, although that has already started with some experimental work I and the other developers have done with the generalized least squares method from nlme. * * *
• Possibly incorporate rstan via rstantools to produce likelihoods and posteriors

If you’d like to help contribute, please see the contributing guide.

R Package Citations

citation("quantreg")

## To cite package 'quantreg' in publications use:
## 
##   Koenker R (2025). _quantreg: Quantile Regression_. R package version
##   6.1, <https://www.r-project.org>.
## 
## A BibTeX entry for LaTeX users is
## 
##   @Manual{,
##     title = {quantreg: Quantile Regression},
##     author = {Roger Koenker},
##     year = {2025},
##     note = {R package version 6.1},
##     url = {https://www.r-project.org},
##   }

citation("nlme")

## To cite package 'nlme' in publications use:
## 
##   Pinheiro J, Bates D, R Core Team (2026). _nlme: Linear and Nonlinear
##   Mixed Effects Models_. doi:10.32614/CRAN.package.nlme
##   <https://doi.org/10.32614/CRAN.package.nlme>. R package version
##   3.1-169, <https://CRAN.R-project.org/package=nlme>.
## 
##   Pinheiro JC, Bates DM (2000). _Mixed-Effects Models in S and S-PLUS_.
##   Springer, New York. doi:10.1007/b98882
##   <https://doi.org/10.1007/b98882>.
## 
## To see these entries in BibTeX format, use 'print(<citation>,
## bibtex=TRUE)', 'toBibtex(.)', or set
## 'options(citation.bibtex.max=999)'.

citation("rstan")

## To cite RStan in publications use:
## 
##   Stan Development Team (2025). RStan: the R interface to Stan. R
##   package version 2.32.7. https://mc-stan.org/.
## 
## A BibTeX entry for LaTeX users is
## 
##   @Misc{,
##     title = {{RStan}: the {R} interface to {Stan}},
##     author = {{Stan Development Team}},
##     note = {R package version 2.32.7},
##     year = {2025},
##     url = {https://mc-stan.org/},
##   }

citation("rstantools")

## To cite package 'rstantools' in publications use:
## 
##   Gabry J, Goodrich B, Lysy M, Johnson A (2026). _rstantools: Tools for
##   Developing R Packages Interfacing with 'Stan'_. R package version
##   2.7.0, <https://mc-stan.org/rstantools/>.
## 
## A BibTeX entry for LaTeX users is
## 
##   @Manual{,
##     title = {rstantools: Tools for Developing R Packages Interfacing with 'Stan'},
##     author = {Jonah Gabry and Ben Goodrich and Martin Lysy and Andrew Johnson},
##     year = {2026},
##     note = {R package version 2.7.0},
##     url = {https://mc-stan.org/rstantools/},
##   }