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) <arXiv:1610.00345> or Meyer, D.W., Statistics and Computing (2017) <doi:10.1007/s11222-017-9751-9> and Meyer, D.W. (2017) <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 ethz.ch> |
| 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: detpack_1.1.3.zip, r-release: detpack_1.1.3.zip, r-oldrel: detpack_1.1.3.zip |
| macOS binaries: | r-release: detpack_1.1.3.tgz, r-oldrel: detpack_1.1.3.tgz |
| Old sources: | detpack archive |
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