Learn R Programming

⚠️There's a newer version (1.2.15) of this package.Take me there.

simStateSpace (version 1.2.12)

Simulate Data from State Space Models

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. This package was designed to generate data for the simulations performed in Pesigan, Russell, and Chow (2025) .

Copy Link

Version

Install

install.packages('simStateSpace')

Monthly Downloads

1,846

Version

1.2.12

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/jeksterslab/simStateSpace

Homepage

https://jeksterslab.github.io/simStateSpace/

Maintainer

Ivan Jacob Agaloos Pesigan

Last Published

October 10th, 2025

Functions in simStateSpace (1.2.12)

Simulate Diagonal Covariance Matrices from the Multivariate Normal Distribution

Simulate Intercept Vectors in a Discrete-Time Vector Autoregressive Model from the Multivariate Normal Distribution

Simulate Intercept Vectors in a Continuous-Time Vector Autoregressive Model from the Multivariate Normal Distribution

Simulate Random Drift Matrices from the Multivariate Normal Distribution

Simulate Intercept Vectors in a Discrete-Time Vector Autoregressive Model from the Multivariate Normal Distribution

Simulate Random Drift Matrices from the Multivariate Normal Distribution and Project to Hurwitz

Simulate Transition Matrices from the Multivariate Normal Distribution

Simulate Covariance Matrices from the Multivariate Normal Distribution

Simulate Transition Matrices from the Multivariate Normal Distribution and Project to Stability

Steady-State Mean Vector for the Observed Variables in the State Space Model

Simulate Data from the Ornstein–Uhlenbeck Model using a State Space Model Parameterization (Fixed Parameters)

SimSSMLinSDEIVary

Simulate Data from the Linear Stochastic Differential Equation Model using a State Space Model Parameterization (Individual-Varying Parameters)

Simulate Data from the Vector Autoregressive Model (Individual-Varying Parameters)

Simulate Data from a State Space Model (Individual-Varying Parameters)

SimSSMLinGrowthIVary

Simulate Data from the Linear Growth Curve Model (Individual-Varying Parameters)

Simulate Data from the Vector Autoregressive Model (Fixed Parameters)

SimSSMLinGrowth

Simulate Data from the Linear Growth Curve Model

Simulate Data from the Ornstein–Uhlenbeck Model using a State Space Model Parameterization (Individual-Varying Parameters)

SimSSMLinSDEFixed

Simulate Data from the Linear Stochastic Differential Equation Model using a State Space Model Parameterization (Fixed Parameters)

Simulate Data from a State Space Model (Fixed Parameters)

TestStationarity

Test Stationarity

print.simstatespace

Print Method for an Object of Class simstatespace

plot.simstatespace

Plot Method for an Object of Class simstatespace

as.matrix.simstatespace

Coerce an Object of Class simstatespace to a Matrix

as.data.frame.simstatespace

Coerce an Object of Class simstatespace to a Data Frame

Test the Drift Matrix

Test Hurwitz Stability of a Drift Matrix

SpectralAbscissa

Spectral Abscissa

simStateSpace-package

simStateSpace: Simulate Data from State Space Models

Spectral Radius

Steady-State Mean Vector for the Latent Variables in the Linear Stochastic Differential Equation Model

Steady-State Mean Vector for the Observed Variables in the Linear Stochastic Differential Equation Model

ProjectToStability

Project Matrix to Stability

Steady-State Mean Vector for the Latent Variables in the State Space Model

ProjectToHurwitz

Project Matrix to Hurwitz Stability

Steady-State Covariance Matrix for the Observed Variables in the State Space Model

Steady-State Covariance Matrix for the Latent Variables in the Linear Stochastic Differential Equation Model

Convert Parameters from the Linear Stochastic Differential Equation Model to State Space Model Parameterization

Steady-State Covariance Matrix for the Latent Variables in the State Space Model

Steady-State Covariance Matrix for the Observed Variables in the Linear Stochastic Differential Equation Model