Package: trajeR 1.0

trajeR: Group Based Modeling Trajectory

Estimation of group-based trajectory models, including finite mixture models for longitudinal data, supporting censored normal, zero-inflated Poisson, logit, and beta distributions, using expectation-maximization and quasi-Newton methods, with tools for model selection, diagnostics, and visualization of latent trajectory groups, <doi:10.4159/9780674041318>, Nagin, D. (2005). Group-Based Modeling of Development. Cambridge, MA: Harvard University Press. and Noel (2022), <https://orbilu.uni.lu/>, thesis.

Authors:Cédric Noel [aut, cre], Jang Schiltz [aut]

trajeR_1.0.tar.gz
trajeR_1.0.zip(r-4.7-x86_64)trajeR_1.0.zip(r-4.7-arm64)trajeR_1.0.zip(r-4.6-x86_64)trajeR_1.0.zip(r-4.6-arm64)trajeR_1.0.zip(r-4.5-x86_64)
trajeR_1.0.tgz(r-4.6-x86_64)trajeR_1.0.tgz(r-4.6-arm64)trajeR_1.0.tgz(r-4.5-x86_64)trajeR_1.0.tgz(r-4.5-arm64)
trajeR_1.0.tar.gz(r-4.7-arm64)trajeR_1.0.tar.gz(r-4.7-x86_64)trajeR_1.0.tar.gz(r-4.6-arm64)trajeR_1.0.tar.gz(r-4.6-x86_64)
trajeR_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
trajeR/json (API)

# Install 'trajeR' in R:
install.packages('trajeR', repos = c('https://gitedric.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://codeberg.org/cidric/trajer

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

openblascppopenmp

5.11 score 16 scripts 461 downloads 18 exports 8 dependencies

Last updated from:05f517cefa. Checks:13 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64ERROR172
linux-devel-x86_64ERROR167
source / vignettesOK455
linux-release-arm64ERROR170
linux-release-x86_64ERROR193
macos-release-arm64ERROR242
macos-release-x86_64ERROR607
macos-oldrel-arm64ERROR259
macos-oldrel-x86_64ERROR432
windows-devel-arm64ERROR418
windows-devel-x86_64ERROR292
windows-release-arm64ERROR386
windows-release-x86_64ERROR190
windows-oldrel-x86_64ERROR225
wasm-releaseOK135

Exports:adequacyAvePPconfidenceIntConfIntTdiffaitbetafaitget_group_probabilitiesGroupProbGroupProfilesOCCplot_trajectory_multplotrajeRpropAssigntrajeRtrajeR_multtrajeRAICtrajeRBICtrajeRSH

Dependencies:capushecliMASSminpack.lmnumDerivRcppRcppArmadilloucminf

Group Based Trajectory Modelling (GBTM)
Introduction | Getting started | Références
Rendered fromtrajeR_vignette.Rmdusingknitr::rmarkdown

Last update: 2026-07-31
Started: 2026-07-26

Logit model
Introduction | Parameters | Plot
Rendered fromLOGIT.Rmdusingknitr::rmarkdown

Last update: 2026-07-31
Started: 2026-07-26

Normal and Censored Normal model
Censored Normal model | Parameters | Likelihood method | EM method | Plot | Adding risk covariate | Adding time covariate | Censored Normal distribution
Rendered fromnormal.Rmdusingknitr::rmarkdown

Last update: 2026-07-31
Started: 2026-07-31

Zero Inflated Poisson model
Parameters | Plot | Adding covariate | Adding time depdendent covariate
Rendered fromZIP.Rmdusingknitr::rmarkdown

Last update: 2026-07-31
Started: 2026-07-31

Readme and manuals

Help Manual

Help pageTopics
Model Adequacy Assessmentadequacy
Average Posterior Probability of AssignmentAvePP
Compute Confidence Intervals for Predicted TrajectoriesconfidenceInt
Bootstrap Confidence Intervals for Group Membership ProbabilitiesConfIntT
Simulated CNORM Datasetdata_CNORM
Simulated Censored CNORM Datasetdata_CNORM_Censored
Simulated LOGIT Datasetdata_LOGIT
Simulated ZIP Datasetdata_ZIP
Simulated CNORM Dataset (data01)dataNORM01
Differentialdiffaitbeta
Function faitfait
Compute Posterior Probabilities and Group Assignments for Multivariate Trajectory Modelsget_group_probabilities
Calculate Posterior Membership ProbabilitiesGroupProb
Generate Group Profiles Based on CovariatesGroupProfiles
Odds of Correct Classification (OCC)OCC
Plot Multivariate Trajectoriesplot_trajectory_mult
Plot Group Trajectories from a trajeR ModelplotrajeR
Plot Method for BETA Trajectory ObjectsplotrajeR.Trajectory.BETA
Plot Method for CNORM Trajectory ObjectsplotrajeR.Trajectory.CNORM
Plot Method for LOGIT Trajectory ObjectsplotrajeR.Trajectory.LOGIT
Plot Method for Non-Linear Trajectory ObjectsplotrajeR.Trajectory.NL
Plot Method for POIS Trajectory ObjectsplotrajeR.Trajectory.POIS
Plot Method for ZIP Trajectory ObjectsplotrajeR.Trajectory.ZIP
Print BETAprint.Trajectory.BETA
Print Method for a `Trajectory.CNORM` Objectprint.Trajectory.CNORM
Print Method for a `Trajectory.LOGIT` Objectprint.Trajectory.LOGIT
Print Method for a `trajectory.mult` Objectprint.trajectory.mult
Print Method for a `Trajectory.NL` Objectprint.Trajectory.NL
Print Method for a `Trajectory.ZIP` Objectprint.Trajectory.POIS
Print ZIPprint.Trajectory.ZIP
Proportion of Individuals Assigned to Each GrouppropAssign
Fitting longitudinal mixture modelstrajeR
Fitting Multivariate Longitudinal Mixture ModelstrajeR_mult
Internal function to fit Beta Regression ModeltrajeR.BETA
Internal function to fit CNORM ModeltrajeR.CNORM
Internal function to fit LOGIT ModeltrajeR.LOGIT
Internal function to fit a Non-Linear ModeltrajeR.NL
Internal function to fit Poisson ModeltrajeR.POIS
Internal function to fit ZIP ModeltrajeR.ZIP
Akaike Information Criterion (AIC) for a Trajectory ObjecttrajeRAIC
Bayesian Information Criterion (BIC) for a Trajectory ObjecttrajeRBIC
Slope Heuristic for Trajectory Model SelectiontrajeRSH