doi:10.18637/jss.v106.i09>); Allegra et al. (2020, <doi:10.1038/s41598-020-72222-0>); Denti et al. (2022, <doi:10.1038/s41598-022-20991-1>); Facco et al. (2017, <doi:10.1038/s41598-017-11873-y>); Santos-Fernandez et al. (2021, <doi:10.1038/s41598-022-20991-1>).">

intRinsic: Likelihood-Based Intrinsic Dimension Estimators (original) (raw)

Provides functions to estimate the intrinsic dimension of a dataset via likelihood-based approaches. Specifically, the package implements the 'TWO-NN' and 'Gride' estimators and the 'Hidalgo' Bayesian mixture model. In addition, the first reference contains an extended vignette on the usage of the 'TWO-NN' and 'Hidalgo' models. References: Denti (2023, <doi:10.18637/jss.v106.i09>); Allegra et al. (2020, <doi:10.1038/s41598-020-72222-0>); Denti et al. (2022, <doi:10.1038/s41598-022-20991-1>); Facco et al. (2017, <doi:10.1038/s41598-017-11873-y>); Santos-Fernandez et al. (2021, <doi:10.1038/s41598-022-20991-1>).

Version: 1.1.1
Depends: R (≥ 4.2.0)
Imports: dplyr, FNN, ggplot2, knitr, latex2exp, Rcpp, reshape2, rlang, stats, utils, salso
LinkingTo: Rcpp, RcppArmadillo
Published: 2025-09-24
DOI: 10.32614/CRAN.package.intRinsic
Author: Francesco Denti ORCID iD [aut, cre, cph], Andrea Gilardi ORCID iD [aut]
Maintainer: Francesco Denti <francescodenti.personal at gmail.com>
BugReports: https://github.com/fradenti/intRinsic/issues
License: MIT + file
URL: https://github.com/Fradenti/intRinsic
NeedsCompilation: yes
Citation: intRinsic citation info
Materials: README, NEWS
CRAN checks: intRinsic results

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