ClustBlock
6.0.0Clustering of Datasets
Overview
Hierarchical and partitioning algorithms to cluster blocks of variables. The partitioning algorithm includes an option called noise cluster to set aside atypical blocks of variables. Different thresholds per cluster can be sets. The CLUSTATIS method (for quantitative blocks) (Llobell, Cariou, Vigneau, Labenne & Qannari (2020) doi:10.1016/j.foodqual.2018.05.013, Llobell, Vigneau & Qannari (2019) doi:10.1016/j.foodqual.2019.02.017) and the CLUSCATA method (for Check-All-That-Apply data) (Llobell, Cariou, Vigneau, Labenne & Qannari (2019) doi:10.1016/j.foodqual.2018.09.006, Llobell, Giacalone, Labenne & Qannari (2019) doi:10.1016/j.foodqual.2019.05.017) are the core of this package. The CATATIS methods allows to compute some indices and tests to control the quality of CATA data (Llobell, Bonnet & Giacalone (2024) doi:10.1111/joss.12941) . Multivariate analysis and clustering of subjects for quantitative multiblock data, CATA, RATA, Free Sorting and JAR experiments are available. Clustering of observations (products in sensory analysis) in multi-block context (notably with ClusMB strategy) is also included (Llobell & Giacalone (2025) doi:10.1111/joss.70024).Performing clustering based on CATA and liking at the same time is possible thanks to cluscata_liking function (Vigneau, Cariou, Giacalone, Berget & Llobell (2022) doi:10.1016/j.foodqual.2021.104358). Clustering of variables (quantitative, qualitative or mixed) can be done thanks to the MixCluStatis() function.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 70%
- Documented parameters
- 98%
- Return-value docs
- 100%
- References docs
- 63%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
Datasets
People & History
19 releases. Pick two to compare their code metrics. R releases are shown for context.
- 6.0.0Latest
- RR 4.6.0 released · 2026-04-24
- 5.0.02026-03-24 · diff ↗
- 4.1.12025-06-11 · diff ↗
- 4.1.02025-05-13 · diff ↗
- RR 4.5.0 released · 2025-04-11
- 4.0.02024-05-21 · diff ↗
- RR 4.4.0 released · 2024-04-24
- 3.2.02023-08-30 · diff ↗
- 3.1.12023-06-29 · diff ↗
- RR 4.3.0 released · 2023-04-21
- 3.1.02023-03-05 · diff ↗
- 3.0.02022-09-08 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 2.4.12022-03-31 · diff ↗
- 2.4.02021-06-22 · diff ↗
Show 12 earlier events
- RR 4.1.0 released · 2021-05-18
- 2.3.12020-11-21 · diff ↗
- 2.3.02020-11-16 · diff ↗
- 2.2.12020-10-02 · diff ↗
- RR 4.0.0 released · 2020-04-24
- 2.2.02020-04-23 · diff ↗
- 2.1.12019-11-29 · diff ↗
- 2.1.02019-11-07 · diff ↗
- 2.0.02019-07-08 · diff ↗
- RR 3.6.0 released · 2019-04-26
- 1.0.02019-03-06
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2019-03-06
- Total releases
- 19 / 7 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5
- Bundled data
- 14 KB / 8 files
- Download size
- 80 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("ClustBlock")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-13, which the citation names so these numbers can be found later. More on citing and the projects behind them.