Package: gbmt 0.1.3
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:
gbmt_0.1.3.tar.gz
gbmt_0.1.3.zip(r-4.5)gbmt_0.1.3.zip(r-4.4)gbmt_0.1.3.zip(r-4.3)
gbmt_0.1.3.tgz(r-4.4-any)gbmt_0.1.3.tgz(r-4.3-any)
gbmt_0.1.3.tar.gz(r-4.5-noble)gbmt_0.1.3.tar.gz(r-4.4-noble)
gbmt_0.1.3.tgz(r-4.4-emscripten)gbmt_0.1.3.tgz(r-4.3-emscripten)
gbmt.pdf |gbmt.html✨
gbmt/json (API)
| # Install 'gbmt' in R: |
| install.packages('gbmt', repos = c('https://alessandromagrini.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:724f053e83. Checks:OK: 3 NOTE: 4. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 20 2024 |
| R-4.5-win | NOTE | Nov 20 2024 |
| R-4.5-linux | NOTE | Nov 20 2024 |
| R-4.4-win | NOTE | Nov 20 2024 |
| R-4.4-mac | NOTE | Nov 20 2024 |
| R-4.3-win | OK | Nov 20 2024 |
| R-4.3-mac | OK | Nov 20 2024 |
