Ivan Jacob Agaloos Pesigan
Description
Provides a streamlined and user-friendly framework for simulating data in state space models, particularly when the number of subjects/units ($`n`$) exceeds one, a scenario commonly encountered in social and behavioral sciences. For an introduction to state space models in social and behavioral sciences, refer to Chow, Ho, Hamaker, and Dolan (2010: https://doi.org/10.1080/10705511003661553).
Installation
You can install the CRAN release of simStateSpace with:
install.packages("simStateSpace")You can install the development version of simStateSpace from GitHub with:
if (!require("remotes")) install.packages("remotes")
remotes::install_github("jeksterslab/simStateSpace")More Information
See GitHub Pages for package documentation.
References
Chow, S.-M., Ho, M. R., Hamaker, E. L., & Dolan, C. V. (2010). Equivalence and differences between structural equation modeling and state-space modeling techniques. Structural Equation Modeling: A Multidisciplinary Journal, 17(2), 303–332. https://doi.org/10.1080/10705511003661553
R Core Team. (2024). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/