Package: fangs 0.2.25

fangs: Feature Allocation Neighborhood Greedy Search Algorithm

A neighborhood-based, greedy search algorithm is performed to estimate a feature allocation by minimizing the expected loss based on posterior samples from the feature allocation distribution. The method is described in Dahl, Johnson, and Andros (2023) "Comparison and Bayesian Estimation of Feature Allocations" <doi:10.1080/10618600.2023.2204136>.

Authors:David B. Dahl [aut, cre], R. Jacob Andros [aut], Devin J. Johnson [aut], Authors of the dependency Rust crates [ctb]

fangs_0.2.25.tar.gz
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fangs_0.2.25.tgz(r-4.6-x86_64)fangs_0.2.25.tgz(r-4.6-arm64)fangs_0.2.25.tgz(r-4.5-x86_64)fangs_0.2.25.tgz(r-4.5-arm64)
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fangs_0.2.25.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
fangs/json (API)

# Install 'fangs' in R:
install.packages('fangs', repos = c('https://dbdahl.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/dbdahl/fangs-package/issues

Datasets:
  • samplesFA - Samples from the Attraction Indian Buffet Distribution

On CRAN:

Conda:

rustcargo

3.95 score 3 stars 1 scripts 413 downloads 3 exports 0 dependencies

Last updated from:29916b1123. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK141
linux-devel-x86_64OK154
source / vignettesOK209
linux-release-arm64OK145
linux-release-x86_64OK148
macos-release-arm64OK125
macos-release-x86_64OK153
macos-oldrel-arm64OK102
macos-oldrel-x86_64OK290
windows-devel-arm64OK217
windows-devel-x86_64OK172
windows-release-arm64OK217
windows-release-x86_64OK121
windows-oldrel-x86_64OK134
wasm-releaseOK144

Exports:compute_expected_losscompute_lossfangs

Dependencies: