raw_kbdm: Kolmogorov complexity of a matrix

In spatialwarnings: Spatial Early Warning Signals of Ecosystem Degradation

Kolmogorov complexity of a matrix

Description

Compute the Kolmogorov complexity of a matrix using the Block Decomposition Method (requires the acss package).

Usage

raw_kbdm(mat, subsize)

Arguments

mat	A logical matrix (with TRUE/FALSE values)
subsize	A submatrix size to carry out the Block Decomposition Method (must be between 1 and 3)

Details

The Kolmogorov complexity cannot be computed directly for large strings (i.e. matrices). However, the complexity of smaller submatrices can be estimated, then combined to obtain an approximation of the complexity of the whole matrix. This method, the Block Decomposition Method is implemented in this function. See also kbdm_sews for more details.

Value

The KBDM numeric value as a named vector

See Also

kbdm_sews, acss

Examples

## Not run:  
raw_kbdm(forestgap[[1]], subsize = 3)

## End(Not run)

spatialwarnings documentation built on March 21, 2022, 5:08 p.m.