simlandr - Simulation-Based Landscape Construction for Dynamical Systems

A toolbox for constructing potential landscapes for dynamical systems using Monte Carlo simulation. The method is based on the potential landscape definition by Wang et al. (2008) <doi:10.1073/pnas.0800579105> (also see Zhou & Li, 2016 <doi:10.1063/1.4943096> for further mathematical discussions) and can be used for a large variety of models.

Last updated 6 months ago

research-tool

5.56 score 6 stars 2 packages 3 scripts 260 downloads

SparseVFC - Sparse Vector Field Consensus for Vector Field Learning

The sparse vector field consensus (SparseVFC) algorithm (Ma et al., 2013 <doi:10.1016/j.patcog.2013.05.017>) for robust vector field learning. Largely translated from the Matlab functions in <https://github.com/jiayi-ma/VFC>.

Last updated 1 years ago

4.48 score 1 stars 1 packages 3 scripts 174 downloads

fitlandr - Fit Vector Fields and Potential Landscapes from Intensive Longitudinal Data

A toolbox for estimating vector fields from intensive longitudinal data, and construct potential landscapes thereafter. The vector fields can be estimated with two nonparametric methods: the Multivariate Vector Field Kernel Estimator (MVKE) by Bandi & Moloche (2018) <doi:10.1017/S0266466617000305> and the Sparse Vector Field Consensus (SparseVFC) algorithm by Ma et al. (2013) <doi:10.1016/j.patcog.2013.05.017>. The potential landscapes can be constructed with a simulation-based approach with the 'simlandr' package (Cui et al., 2021) <doi:10.31234/osf.io/pzva3>, or the Bhattacharya et al. (2011) method for path integration <doi:10.1186/1752-0509-5-85>.

Last updated 1 months ago

3.48 score 2 stars 4 scripts 175 downloads

Isinglandr - Landscape Construction and Simulation for Ising Networks

A toolbox for constructing potential landscapes for Ising networks. The parameters of the networks can be directly supplied by users or estimated by the 'IsingFit' package by van Borkulo and Epskamp (2016) <https://CRAN.R-project.org/package=IsingFit> from empirical data. The Ising model's Boltzmann distribution is preserved for the potential landscape function. The landscape functions can be used for quantifying and visualizing the stability of network states, as well as visualizing the simulation process.

Last updated 2 months ago

3.30 score 1 stars 3 scripts 157 downloads

NVAR - Nonlinear Vector Autoregression Models

Estimate nonlinear vector autoregression models (also known as the next generation reservoir computing) for nonlinear dynamic systems. The algorithm was described by Gauthier et al. (2021) <doi:10.1038/s41467-021-25801-2>.

Last updated 10 months ago

3.18 score 4 scripts 193 downloads

quadVAR - Quadratic Vector Autoregression

Estimate quadratic vector autoregression models with the strong hierarchy using the RAMP algorithm, compare the performance with linear models, and construct networks with partial derivatives.

Last updated 7 days ago

2.93 score 3 scripts