Data

Tools

Indexes

Applications

Experiments

Open Source Science

latrend

An R package for clustering longitudinal datasets in a standardized way, providing interfaces to various R packages for longitudinal clustering, and facilitating the rapid implementation and evaluation of new methods

https://github.com/niekdt/latrend

Science Score: 54.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ✓
    Academic publication links
    Links to: arxiv.org
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (18.8%) to scientific vocabulary

Keywords

cluster-analysis clustering-evaluation clustering-methods data-science longitudinal-clustering longitudinal-data mixture-models r r-package time-series-analysis
Last synced: 6 months ago · JSON representation ·

Repository

An R package for clustering longitudinal datasets in a standardized way, providing interfaces to various R packages for longitudinal clustering, and facilitating the rapid implementation and evaluation of new methods

Basic Info
Statistics
  • Stars: 34
  • Watchers: 3
  • Forks: 5
  • Open Issues: 18
  • Releases: 23
Topics
cluster-analysis clustering-evaluation clustering-methods data-science longitudinal-clustering longitudinal-data mixture-models r r-package time-series-analysis
Created over 5 years ago · Last pushed 8 months ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

latrend

R-CMD-check CRAN Lifecycle: maturing <!-- Codecov test coverage --> Downloads <!-- badges: end --> The latrend package provides a framework for clustering longitudinal datasets in a standardized way. The name is short for latent-class trend (analysis), referring to the discovery of hidden trends in the data. The package provides interfaces to various R packages for conducting this type of analysis.

The package is described in detail in the pre-print available at https://arxiv.org/abs/2402.14621

Features

  • Unified cluster analysis, independent of the underlying algorithms used. Enabling users to compare the performance of various longitudinal cluster methods on the case study at hand.
  • Supports many different methods for longitudinal clustering out of the box (see the list of supported packages below).
  • The framework consists of extensible S4 methods based on an abstract model class, enabling rapid prototyping of new cluster methods or model specifications.
  • Standard plotting tools for model evaluation across methods (e.g., trajectories, cluster trajectories, model fit, metrics)
  • Support for many cluster metrics through the packages clusterCrit, mclustcomp, and igraph.
  • The structured and unified analysis approach enables simulation studies for comparing methods.
  • Standardized model validation for all methods through bootstrapping or k-fold cross-validation.

See the release notes page for the latest updates.

Installation

The latest release of latrend can be installed from CRAN by running: R install.packages("latrend")

It can also be installed from Github directly using: ```R remotes::installgithub('niekdt/latrend', ref = remotes::githubrelease())

include vignettes

remotes::installgithub('niekdt/latrend', ref = remotes::githubrelease(), build_vignettes = TRUE) ```

Usage

R library(latrend) Load and view example data. R data(latrendData) head(latrendData) options(latrend.id = "Id", latrend.time = "Time") plotTrajectories(latrendData, response = "Y") image

Cluster the trajectories and plot the results. R kmlMethod <- lcMethodKML("Y", nClusters = 3) model <- latrend(kmlMethod, data = latrendData) summary(model) plot(model) image

Identify solutions for 1 to 5 clusters. R kmlMethods <- lcMethods(kmlMethod, nClusters = 1:5) models <- latrendBatch(kmlMethods, data = latrendData)

Determine the number of clusters through one or more internal cluser metrics. R metric(models, c("WMAE", "BIC")) plotMetric(models, c("Dunn", "ASW", "WMAE", "WRSS", "BIC", "estimationTime")) image

Supported packages

The latrend package provides interfaces to the relevant methods for longitudinal clustering for the following packages: * akmedoids * crimCV * dtwclust * fda * flexmix * funFEM * kml * lcmm * mclust * mixAK * mixtools

Contributing

We appreciate any contributions in the form of ideas, feature requests, bug reports, bug fixes, documentation improvements, code reformatting, and code submissions. Please see the Contributing guide.

Owner

  • Name: Niek Den Teuling
  • Login: niekdt
  • Kind: user
  • Location: Eindhoven, the Netherlands
  • Company: Philips Research

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Den Teuling"
  given-names: "Niek"
  orcid: "https://orcid.org/0000-0003-1026-5080"
- family-names: "Pauws"
  given-names: "Steffen"
  orcid: "https://orcid.org/0000-0003-2257-9239"
- family-names: "van den Heuvel"
  given-names: "Edwin"
  orcid: "https://orcid.org/0000-0001-9157-7224"
title: "latrend: A Framework for Clustering Longitudinal Data"
version: 1.6.2
date-released: 2025-06-30
url: "https://github.com/niekdt/latrend"

GitHub Events

Total
  • Release event: 1
  • Watch event: 1
  • Push event: 7
  • Create event: 1
Last Year
  • Release event: 1
  • Watch event: 1
  • Push event: 7
  • Create event: 1

Committers

Last synced: 8 months ago

All Time
  • Total Commits: 1,317
  • Total Committers: 3
  • Avg Commits per committer: 439.0
  • Development Distribution Score (DDS): 0.31
Past Year
  • Commits: 14
  • Committers: 1
  • Avg Commits per committer: 14.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Niek Den Teuling n****g@p****m 909
Niek Den Teuling n****e@n****e 407
olivroy 5****y 1
Committer Domains (Top 20 + Academic)
philips.com: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 92
  • Total pull requests: 8
  • Average time to close issues: about 1 month
  • Average time to close pull requests: about 2 hours
  • Total issue authors: 15
  • Total pull request authors: 2
  • Average comments per issue: 1.36
  • Average comments per pull request: 0.75
  • Merged pull requests: 7
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 5
  • Pull requests: 0
  • Average time to close issues: 2 months
  • Average time to close pull requests: N/A
  • Issue authors: 4
  • Pull request authors: 0
  • Average comments per issue: 2.4
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • niekdt (61)
  • hichew22 (5)
  • zh-zhang1984 (2)
  • yuwenhuang717 (1)
  • Leprechault (1)
  • janstochl (1)
  • knokknok (1)
  • thomasp85 (1)
Pull Request Authors
  • niekdt (7)
  • olivroy (1)
Top Labels
Issue Labels
enhancement (45) bug (20) documentation (3) wontfix (2) good first issue (2) question (1)
Pull Request Labels
enhancement (4) bug (1)

Packages

  • Total packages: 1
  • Total downloads:
    • cran 502 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 13
  • Total maintainers: 1
cran.r-project.org: latrend

A Framework for Clustering Longitudinal Data

  • Versions: 13
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 502 Last month
Rankings
Forks count: 12.8%
Stargazers count: 13.3%
Average: 23.4%
Downloads: 25.8%
Dependent packages count: 29.8%
Dependent repos count: 35.5%
Maintainers (1)
niek.den.teuling@philips.com
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.6.0 depends
  • R.utils * imports
  • Rdpack * imports
  • assertthat >= 0.2.1 imports
  • data.table >= 1.12.0 imports
  • foreach * imports
  • magrittr * imports
  • matrixStats * imports
  • methods * imports
  • rlang * imports
  • rmarkdown >= 1.18 imports
  • stats * imports
  • akmedoids >= 1.3.0 suggests
  • caret * suggests
  • clusterCrit * suggests
  • covr * suggests
  • crimCV * suggests
  • devtools * suggests
  • doParallel * suggests
  • dplyr * suggests
  • dtwclust * suggests
  • evaluate * suggests
  • fda * suggests
  • flexmix * suggests
  • funFEM * suggests
  • ggplot2 * suggests
  • gridExtra * suggests
  • igraph * suggests
  • kml >= 2.4.1 suggests
  • knitr >= 1.24 suggests
  • lcmm >= 1.9.3 suggests
  • lintr * suggests
  • lme4 * suggests
  • longitudinalData >= 2.4.1 suggests
  • mclust * suggests
  • mclustcomp * suggests
  • mixAK * suggests
  • mixtools * suggests
  • pkgdown * suggests
  • psych * suggests
  • qqplotr * suggests
  • rcmdcheck * suggests
  • roxygen2 >= 7.1.0 suggests
  • simTool * suggests
  • testthat >= 3.0.0 suggests
  • tibble * suggests
  • tinytex * suggests
.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v2 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-renv v2 composite
  • r-lib/actions/setup-tinytex v1 composite
.github/workflows/pkgdown.yaml actions
  • actions/checkout v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-renv v2 composite
.github/workflows/test-coverage.yaml actions
  • actions/checkout v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-renv v2 composite