Package: gbmt 0.1.4

gbmt: Group-Based Multivariate Trajectory Modeling

Estimation and analysis of group-based multivariate trajectory models (Nagin, 2018 <doi:10.1177/0962280216673085>; Magrini, 2022 <doi:10.1007/s10182-022-00437-9>). The package implements an Expectation-Maximization (EM) algorithm allowing unbalanced panel and missing values, and provides several functionalities for prediction and graphical representation.

Authors:Alessandro Magrini [aut, cre]

gbmt_0.1.4.tar.gz
gbmt_0.1.4.zip(r-4.7)gbmt_0.1.4.zip(r-4.6)gbmt_0.1.4.zip(r-4.5)
gbmt_0.1.4.tgz(r-4.6-any)gbmt_0.1.4.tgz(r-4.5-any)
gbmt_0.1.4.tar.gz(r-4.7-any)gbmt_0.1.4.tar.gz(r-4.6-any)
gbmt_0.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
gbmt/json (API)

# Install 'gbmt' in R:
install.packages('gbmt', repos = c('https://alessandromagrini.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • achievement - Achievement tests for children
  • agrisus - EU agricultural sustainability data
  • agrisus2 - EU agricultural sustainability data

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.93 score 5 stars 17 scripts 590 downloads 1 mentions 2 exports 2 dependencies

Last updated from:8753e7447f. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK159
source / vignettesOK221
linux-release-x86_64OK126
macos-release-arm64OK182
macos-oldrel-arm64OK180
windows-develOK98
windows-releaseOK81
windows-oldrelOK93
wasm-releaseOK108

Exports:gbmtposterior

Dependencies:latticeMatrix