Package: simStateSpace 1.2.10

Ivan Jacob Agaloos Pesigan

simStateSpace: Simulate Data from State Space Models

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) <doi:10.1080/10705511003661553>.

Authors:Ivan Jacob Agaloos Pesigan [aut, cre, cph]

simStateSpace_1.2.10.tar.gz
simStateSpace_1.2.10.tar.gz(r-4.5-noble)simStateSpace_1.2.10.tar.gz(r-4.4-noble)
simStateSpace_1.2.10.tgz(r-4.4-emscripten)simStateSpace_1.2.10.tgz(r-4.3-emscripten)
simStateSpace.pdf |simStateSpace.html✨
simStateSpace/json (API)
NEWS

# Install 'simStateSpace' in R:
install.packages('simStateSpace', repos = 'https://cloud.r-project.org')

Bug tracker:https://github.com/jeksterslab/simstatespace/issues

Pkgdown site:https://jeksterslab.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

2.62 score 2 packages 319 downloads 18 exports 2 dependencies

Last updated 4 days agofrom:0f5b1a9053. Checks:3 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 30 2025
R-4.5-linux-x86_64OKMar 30 2025
R-4.4-linux-x86_64OKMar 30 2025

Exports:LinSDE2SSMLinSDECovLinSDEMeanSimBetaNSimPhiNSimSSMFixedSimSSMIVarySimSSMLinGrowthSimSSMLinGrowthIVarySimSSMLinSDEFixedSimSSMLinSDEIVarySimSSMOUFixedSimSSMOUIVarySimSSMVARFixedSimSSMVARIVaryTestPhiTestStabilityTestStationarity

Dependencies:RcppRcppArmadillo

Citation

To cite simStateSpace in publications, please use:

Pesigan, I. J. A. (2024). simStateSpace: Simulate Data from State Space Models. R package version 1.2.10. https://github.com/jeksterslab/simStateSpace

Corresponding BibTeX entry: 

  @Manual{,
    author = {Ivan Jacob Agaloos Pesigan},
    title = {simStateSpace: Simulate Data from State Space Models},
    year = {2024},
    note = {R package version 1.2.10},
  }

Readme and manuals

Help Manual

Help pageTopics
Coerce an Object of Class 'simstatespace' to a Data Frameas.data.frame.simstatespace
Coerce an Object of Class 'simstatespace' to a Matrixas.matrix.simstatespace
Convert Parameters from the Linear Stochastic Differential Equation Model to State Space Model ParameterizationLinSDE2SSM
Steady-State Covariance Matrix for the Linear Stochastic Differential Equation ModelLinSDECov
Steady-State Mean Vector for the Linear Stochastic Differential Equation ModelLinSDEMean
Plot Method for an Object of Class 'simstatespace'plot.simstatespace
Print Method for an Object of Class 'simstatespace'print.simstatespace
Simulate Transition Matrices from the Multivariate Normal DistributionSimBetaN
Simulate Random Drift Matrices from the Multivariate Normal DistributionSimPhiN
Simulate Data from a State Space Model (Fixed Parameters)SimSSMFixed
Simulate Data from a State Space Model (Individual-Varying Parameters)SimSSMIVary
Simulate Data from the Linear Growth Curve ModelSimSSMLinGrowth
Simulate Data from the Linear Growth Curve Model (Individual-Varying Parameters)SimSSMLinGrowthIVary
Simulate Data from the Linear Stochastic Differential Equation Model using a State Space Model Parameterization (Fixed Parameters)SimSSMLinSDEFixed
Simulate Data from the Linear Stochastic Differential Equation Model using a State Space Model Parameterization (Individual-Varying Parameters)SimSSMLinSDEIVary
Simulate Data from the Ornstein–Uhlenbeck Model using a State Space Model Parameterization (Fixed Parameters)SimSSMOUFixed
Simulate Data from the Ornstein–Uhlenbeck Model using a State Space Model Parameterization (Individual-Varying Parameters)SimSSMOUIVary
Simulate Data from the Vector Autoregressive Model (Fixed Parameters)SimSSMVARFixed
Simulate Data from the Vector Autoregressive Model (Individual-Varying Parameters)SimSSMVARIVary
Test the Drift MatrixTestPhi
Test StabilityTestStability
Test StationarityTestStationarity