Fit Vector Fields and Potential Landscapes from Intensive Longitudinal Data
Add a grid to a vectorfield object to enable linear interpolation
Align potential values
A fast bilinear interpolation function
Find equilibrium points for a vector field
Estimate a 2D vector field
Estimate a 3D potential landscape from a vector field
fitlandr: Fit Vector Fields and Potential Landscapes from Intensive Lo...
Multivariate vector field kernel estimator
Return a normalized prediction function
Bhattacharya method for path integration
Options controlling the path-integral algorithm
Pipe operator
Plot a 2D vector field
Calculate the vector value at a given position
Reorder a simulation output in time order
Simulation from vector fields
Options controlling the vector field simulation
Options controlling the landscape construction
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>.
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