compute_smap_matrices: Generate the matrices of S-map coefficients

In ha0ye/portalDS: Compute Dynamic Stability for Rodents at Portal

Description

Using the S-map coefficients, assemble the appropriate Jacobian matrices for each time point

Usage

compute_smap_matrices(smap_coeffs, ccm_links)

Arguments

smap_coeffs	A list of the S-map coefficients for each predictor variable (as returned from compute_smap_coeffs())
ccm_links	A data.frame containing the significant causal links. Each row is a causal link. The columns are: xmap_from the column index of the predictor variable in CCM xmap_to the column index of the predicted variable in CCM best_E the best embedding dimension for CCM

Details

See compute_smap_coeffs() for details on the input data. Let the variables in the system be x^i with i = 1..N. For the S-map model predicting x^it+1, let the coefficient corresponding to variable x^j at lag tau be c^tauij. Then the Jacobian is the block matrix, J =

C^0	C^1	...	C^(d-1)	C^d
I	0	...	0	0
0	I	...	0	0
...	...	...	...	...
0	0	...	I	0

where d is the maximum lag, and C^tau is the matrix formed by the values c^tau_ij. (Note that many of these values will be 0.)

This function computes J at each time step.

Value

A list with the matrix of smap-coefficients at each time point

ha0ye/portalDS documentation built on March 28, 2020, 1:21 p.m.