https://github.com/jeksterslab/simstatespace

simStateSpace: Simulate Data from State Space Models (Pesigan, Russell, & Chow, 2025: https://doi.org/10.1037/met0000779).
https://github.com/jeksterslab/simstatespace

r r-package simulation state-space-model

Last synced: 5 days ago
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simStateSpace: Simulate Data from State Space Models (Pesigan, Russell, & Chow, 2025: https://doi.org/10.1037/met0000779).

• Host: GitHub
• URL: https://github.com/jeksterslab/simstatespace
• Owner: jeksterslab
• License: gpl-3.0
• Created: 2023-11-08T23:50:40.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2026-01-11T04:45:26.000Z (15 days ago)
• Last Synced: 2026-01-11T11:59:16.867Z (15 days ago)
• Topics: r, r-package, simulation, state-space-model
• Language: TeX
• Homepage: https://jeksterslab.github.io/simStateSpace/
• Size: 1.29 GB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS.md
  • License: LICENSE.md
  • Citation: CITATION.cff

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README

          
simStateSpace

================

Ivan Jacob Agaloos Pesigan

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## 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:

).

## Installation

You can install the CRAN release of `simStateSpace` with:

``` r

install.packages("simStateSpace")

```

You can install the development version of `simStateSpace` from

[GitHub](https://github.com/jeksterslab/simStateSpace) with:

``` r

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

remotes::install_github("jeksterslab/simStateSpace")

```

## More Information

See [GitHub Pages](https://jeksterslab.github.io/simStateSpace) 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.





R Core Team. (2024). *R: A language and environment for statistical

computing*. R Foundation for Statistical Computing.