Characteristic-Function De-Heaping Density Estimation R package adheaping version 1.0.0 Tuning-free kernel density estimation for heaped and rounded data using a characteristic-function theory of heaping. Rounding to a grid is convolution with a box followed by lattice sampling, so the density is recovered by deconvolving the known box and tapering against a data-driven noise floor. Provides a box-deconvolution de-heaping estimator, a superposition variant, and a single combined estimator selected by a band-capacity gate; blind grid, heaped-fraction, and mixed-grain readers; and a spectral higher-order comb detector. Faithful base-R replicas of the Heitjan-Rubin multiple-imputation and measurement-error deconvolution methods are included for comparison, and the 'Kernelheaping' stochastic expectation-maximization estimator is used when installed. Software Depends: R (>= 3.6) Imports: stats Suggests: Kernelheaping, foreign, testthat (>= 3.0.0), knitr, rmarkdown Mitchell A. Thornton <mitchat@sbcglobal.net> Comprehensive R Archive Network (CRAN) Mitchell A. Thornton [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=adheaping/LICENSE) 2026-07-24 application/tgz https://CRAN.R-project.org/package=adheaping doi:10.32614/CRAN.package.adheaping