Bayesian Consensus Clustering for Multiple Longitudinal Features
Overview
It is very common nowadays for a study to collect multiple features and appropriately integrating multiple longitudinal features simultaneously for defining individual clusters becomes increasingly crucial to understanding population heterogeneity and predicting future outcomes. 'BCClong' implements a Bayesian consensus clustering (BCC) model for multiple longitudinal features via a generalized linear mixed model. Compared to existing packages, several key features make the 'BCClong' package appealing: (a) it allows simultaneous clustering of mixed-type (e.g., continuous, discrete and categorical) longitudinal features, (b) it allows each longitudinal feature to be collected from different sources with measurements taken at distinct sets of time points (known as irregularly sampled longitudinal data), (c) it relaxes the assumption that all features have the same clustering structure by estimating the feature-specific (local) clusterings and consensus (global) clustering.
Install
Health
ERRORpackage dependenciesr-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-release-macos-arm64, r-release-macos-x86_64
Package required but not available: ‘mixAK’ See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’ manual.
- ERROR9 OK, 4 ERRORNow
- ERROR8 OK, 1 NOTE, 5 ERROR2026-03-10
Documentation
- Help pages
- 16
- Examples that run
- 100%16 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 93%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing BCClong adds 48 packages (28 with compiled code, 41 MB of source tarballs). Heaviest: ggplot2 6.0 MB, lme4 4.3 MB, mclust 2.7 MB.
Code & Tests
Datasets
People & History
Package metadata
- First published
- 2023-01-13
- Total releases
- 4 / 3 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 3.2 MB / 9 files
- Download size
- 4.0 MB
Cite
Cite this package
Run in R for the authors' entry:
citation("BCClong")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.48550/arxiv.2210.08385.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.