The software is related to the subject of Nonparametric Estimation under Shape Constraints.

A description of the content of the software is given in: Software.pdf.

Kim Hendrickx and I wrote the R package curstatCI, for constructing pointwise bootstrap confidence intervals in the current status model. This was originally written in C++ and transferrred to an R package using Rcpp. In doing this, we profited a lot from the book "R packages" by Hadley Wickham. We use the nonparametric bootstrap, resampling the pairs (T_i,Delta_i), but not using (directly) the nonparametric MLE, for which the nonparametric bootstrap fails. See: The nonparametric bootstrap for the current status model.

In the preface of the book with co-author Geurt Jongbloed: Nonparametric Estimation under Shape Constraints it was announced that the computer programs related to the subject of the book and written by us, would be made available via the website http://statistics.tudelft.nl/CUPbook
Work on this has started now. A description of what has presently been done is given in Software.pdf.

The C/C++ programs below are made available to R users by having linked the C++ files to R via Rcpp, and also by Macintosh GUI (Graphical User Interface) applications and terminal applications for Mac OS X and Windows. The Macintosh GUI application compriskMacGui.app for the competing risk model for current status data can be found in the main directory of the compressed folder of directories compriskGUI.tar.gz, which also contains the source files of the application.
The menu of the application allows one to choose the input file, the number of bootstrap samples and confidence intervals for subdistribution functions or hazards. Both the grouped and ungrouped input file formats can be used. A progress bar and counter keep track of the number of bootstrap samples that have been treated.
One can rebuild the corresponding Xcode project it contains on each recent Mac OS X system.

Simulations for confidence intervals in the current status model, based on the SMLE, can be reproduced by using either the executable curstat_bootstrap_simulation, given in curstat_bootstrap.tar.gz (for Mac, an Xcode project), or the executable curstat.exe in curstat_bootstrapsim.zip (for Windows, a Microsoft Visual C++ 2013 project), or by compiling the corresponding Xcode and MSVC++ projects under Mac or Windows, respectively, and running the program from the project.
The corresponding theory is given in Section 9.5 of the book and the paper Nonparametric confidence intervals for monotone functions (2015), Piet Groeneboom and Geurt Jongbloed Annals of Statistics Volume 43, Number 5 (2015), 2019-2054.

The R scripts, using Rcpp to translate the C/C++ code to R, are given in Rcpp Scripts (GitHub).

Simple R scripts, not using Rcpp, will be kept in Simple_Rscripts (GitHub).