tiltdens: Tilted and Data-Sharpened Nonparametric Density Estimation

High-order nonparametric density estimators built by perturbing a conventional kernel estimator, either by re-weighting the observations ("tilting") or by moving them ("data sharpening"). The perturbation is chosen so that the estimator inherits the fast convergence rate of an infinite-order kernel estimator, such as the sinc or trapezoidal flat-top estimator, while remaining a proper non-negative density without the oscillatory tails those estimators suffer from. Two criteria are provided: minimising the L2 distance to an infinite-order comparator, following Doosti and Hall (2016) <doi:10.1111/rssb.12112>, and minimising a cross-validation criterion that needs no comparator and is much faster, following Doosti, Hall and Mateu (2018) <doi:10.1016/j.jspi.2017.12.003>.

Version:	0.1.1
Depends:	R (≥ 3.5.0)
Imports:	graphics, stats, quadprog
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-09-21
DOI:	10.32614/CRAN.package.tiltdens (may not be active yet)
Author:	Hassan Doosti [aut, cre, cph]
Maintainer:	Hassan Doosti <hassan.doosti at mq.edu.au>
BugReports:	https://github.com/DoostiH/tiltdens/issues
License:	MIT + file LICENSE
URL:	https://github.com/DoostiH/tiltdens
NeedsCompilation:	no
Language:	en-GB
Materials:	NEWS
CRAN checks:	tiltdens results

Documentation:

Reference manual:	tiltdens.html , tiltdens.pdf
Vignettes:	Tilted and data-sharpened density estimation (source, R code)

Downloads:

Package source:	tiltdens_0.1.1.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): tiltdens_0.1.1.tgz, r-release (x86_64): tiltdens_0.1.1.tgz, r-oldrel (x86_64): tiltdens_0.1.1.tgz

Linking:

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