Package: tiltdens
Type: Package
Title: Tilted and Data-Sharpened Nonparametric Density Estimation
Version: 0.1.1
Authors@R: person("Hassan", "Doosti", email = "hassan.doosti@mq.edu.au",
                  role = c("aut", "cre", "cph"))
Description: 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>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 3.5.0)
Imports: graphics, stats, quadprog
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.3.1
Config/testthat/edition: 3
URL: https://github.com/DoostiH/tiltdens
BugReports: https://github.com/DoostiH/tiltdens/issues
NeedsCompilation: no
Packaged: 2026-09-10 23:52:21 UTC; MQ20173444
Author: Hassan Doosti [aut, cre, cph]
Maintainer: Hassan Doosti <hassan.doosti@mq.edu.au>
Repository: CRAN
Date/Publication: 2026-09-21 17:10:02 UTC
