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Ivan Jacob Agaloos Pesigan


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:


You can install the CRAN release of simStateSpace with:


You can install the development version of simStateSpace from GitHub with:

if (!require("remotes")) install.packages("remotes")

More Information

See GitHub Pages for package documentation.


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.
R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing.