detpack: Density Estimation and Random Number Generation with Distribution Element Trees

Density estimation for possibly large data sets and conditional/unconditional random number generation or bootstrapping with distribution element trees. The function 'det.construct' translates a dataset into a distribution element tree. To evaluate the probability density based on a previously computed tree at arbitrary query points, the function 'det.query' is available. The functions 'det1' and 'det2' provide density estimation and plotting for one- and two-dimensional datasets. Conditional/unconditional smooth bootstrapping from an available distribution element tree can be performed by 'det.rnd'. For more details on distribution element trees, see: Meyer, D.W. (2016) <doi:10.48550/arXiv.1610.00345> or Meyer, D.W., Statistics and Computing (2017) <doi:10.1007/s11222-017-9751-9> and Meyer, D.W. (2017) <doi:10.48550/arXiv.1711.04632> or Meyer, D.W., Journal of Computational and Graphical Statistics (2018) <doi:10.1080/10618600.2018.1482768>.

Version: 1.1.3
Imports: parallel, graphics, grDevices, stats
Published: 2019-07-24
Author: Daniel Meyer
Maintainer: Daniel Meyer <meyerda at>
License: GPL-2
NeedsCompilation: no
Materials: NEWS
CRAN checks: detpack results


Reference manual: detpack.pdf


Package source: detpack_1.1.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): detpack_1.1.3.tgz, r-oldrel (arm64): detpack_1.1.3.tgz, r-release (x86_64): detpack_1.1.3.tgz, r-oldrel (x86_64): detpack_1.1.3.tgz
Old sources: detpack archive


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