Nothing
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 (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>).
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Francesco Denti [aut, cre, cph] (<https://orcid.org/0000-0003-2978-4702>), Andrea Gilardi [aut] (<https://orcid.org/0000-0002-9424-7439>) |
| Maintainer | Francesco Denti <francescodenti.personal@gmail.com> |
| License | MIT + file LICENSE |
| Version | 1.1.0 |
| URL | https://github.com/Fradenti/intRinsic |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the intRinsic package in your browser
Any scripts or data that you put into this service are public.
