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Density Estimation and Random Number Generation with Distribution Element Trees

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Distribution element trees (DETs) enable the estimation of probability densities based on (possibly large) datasets. Moreover, DETs can be used for random number generation or smooth bootstrapping both in unconditional and conditional modes. In the latter mode, information about certain probability-space components is taken into account when sampling the remaining probability-space components. For details see http://dx.doi.org/10.1007/s11222-017-9751-9 or http://arxiv.org/abs/1610.00345 and http://arxiv.org/abs/1711.04632

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Updates

2.3

performance improvements

2.2

added random number generation functionality

2.1

bug fix in detconstruct.m

2.0

faster parallelized version of DET estimator

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