swMATH ID: 34605
Software Authors: Pavlichin, Dmitri S.; Jiao, Jiantao; Weissman, Tsachy
Description: Approximate profile maximum likelihood. We propose an efficient algorithm for approximate computation of the profile maximum likelihood (PML), a variant of maximum likelihood maximizing the probability of observing a sufficient statistic rather than the empirical sample. The PML has appealing theoretical properties, but is difficult to compute exactly. Inspired by observations gleaned from exactly solvable cases, we look for an approximate PML solution, which, intuitively, clumps comparably frequent symbols into one symbol. This amounts to lower-bounding a certain matrix permanent by summing over a subgroup of the symmetric group rather than the whole group during the computation. We extensively experiment with the approximate solution, and the empirical performance of our approach is competitive and sometimes significantly better than state-of-the-art performances for various estimation problems.
Homepage: https://arxiv.org/abs/1712.07177
Source Code:  https://github.com/dmitrip/PML
Keywords: profile maximum likelihood; dynamic programming; sufficient statistic; partition of multi-partite numbers; integer partition
Related Software: SEPP; Bioconductor; Wasserstein GAN; Ckmeans.1d.dp; GitHub; OEIS
Cited in: 3 Documents

Standard Articles

1 Publication describing the Software, including 1 Publication in zbMATH Year
Approximate profile maximum likelihood. Zbl 1441.62041
Pavlichin, Dmitri S.; Jiao, Jiantao; Weissman, Tsachy

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