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BCClong  

Bayesian Consensus Clustering for Multiple Longitudinal Features
View on CRAN: Click here


Download and install BCClong package within the R console
Install from CRAN:
install.packages("BCClong")

Install from Github:
library("remotes")
install_github("cran/BCClong")

Install by package version:
library("remotes")
install_version("BCClong", "1.0.2")



Attach the package and use:
library("BCClong")
Maintained by
Zhiwen Tan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-01-13
Latest Update: 2024-02-05
Description:
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.
How to cite:
Zhiwen Tan (2023). BCClong: Bayesian Consensus Clustering for Multiple Longitudinal Features. R package version 1.0.2, https://cran.r-project.org/web/packages/BCClong
Previous versions and publish date:
1.0.0 (2023-01-13 10:30), 1.0.1 (2023-08-08 12:10)
Other packages that cited BCClong R package
View BCClong citation profile
Other R packages that BCClong depends, imports, suggests or enhances
Functions, R codes and Examples using the BCClong R package
Some associated functions: BCC.multi . BayesT . model.selection.criteria . traceplot . trajplot . 
Some associated R codes: DiscrepancyMeasure.R . RcppExports.R . Traceplot.R . Trajplot.R . bccLong.R . modelSelection.R .  Full BCClong package functions and examples
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