gbmt-package

Group-Based Multivariate Trajectory Modeling

Estimation and analysis of group-based multivariate trajectory models. package

Details

Package:	gbmt
Type:	Package
Version:	0.1.4
Date:	2024-12-02
License:	GPL-2

Group-based trajectory modeling is a statistical method to determine groups of units based on the trend of a multivariate time series. It is a special case of latent class growth curves where the units in the same group have the same trajectory (Nagin, 2005), but it assumes a multivariate polynomial regression on time within each group, instead of a univariate one, to account for multiple indicators (Nagin et al., 2018; Magrini, 2022). A group-based multivariate trajectory model is estimated through the Expectation-Maximization (EM) algorithm, which allows unbalanced panel and missing values. The main functions currently implemented in the package are:

• gbmt : to estimate a group-based multivariate trajectory model;
• predict.gbmt : to perform prediction on trajectories;
• plot.gbmt : to display estimated and predicted trajectories;
• posterior : to compute posterior probabilities for new units.

Author(s)

Alessandro Magrini alessandro.magrini@unifi.it

References

A. Magrini (2022). Assessment of agricultural sustainability in European Union countries: A group-based multivariate trajectory approach. AStA Advances in Statistical Analysis, 106, 673-703. DOI: 10.1007/s10182-022-00437-9

D. S. Nagin, B. L. Jones, V. L. Passos and R. E. Tremblay (2018). Group-based multi-trajectory modeling. Statistical Methods in Medical Research, 27(7): 2015-2023. DOI: 10.1177/0962280216673085

D. S. Nagin (2005). Group-based modeling of development. Harvard University Press, Cambridge, US-MA.