Package: detpack 1.1.3

Daniel Meyer

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) <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>.

Authors:Daniel Meyer

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Last updated 5 years agofrom:f4f7d4e586. Checks:OK: 2. Indexed: yes.

Exports:det.constructdet.cutdet.dedet.leafsdet.querydet.rnddet1det2

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