intRinsic: Likelihood-Based Intrinsic Dimension Estimators
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 (2022+, <arXiv:2102.11425>);
Allegra et al. (2020, <doi:10.1038/s41598-020-72222-0>);
Denti et al. (2022+, <arXiv:2104.13832>);
Facco et al. (2017, <doi:10.1038/s41598-017-11873-y>);
Santos-Fernandez et al. (2021, <arXiv:1902.10459>).
| Version: |
0.2.1 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
dplyr, FNN, ggplot2, knitr, latex2exp, MCMCpack, Rcpp, reshape2, rlang, salso, stats, utils |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Published: |
2022-05-31 |
| Author: |
Francesco Denti 
[aut, cre, cph],
Andrea Gilardi
[aut] |
| Maintainer: |
Francesco Denti <francescodenti.personal at gmail.com> |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/Fradenti/intRinsic |
| NeedsCompilation: |
yes |
| Citation: |
intRinsic citation info |
| Materials: |
README NEWS |
| CRAN checks: |
intRinsic results |
Documentation:
Downloads:
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