Select Variable Subsets with Low Correlation or Association (Matrix Interface)

Identifies all maximal subsets of variables from a symmetric matrix (typically a correlation matrix) such that all pairwise absolute values stay below a specified threshold. Implements exact algorithms such as Eppstein–Löffler–Strash (ELS) and Bron–Kerbosch (with or without pivoting).

Usage

MatSelect(mat, threshold = 0.7, method = NULL, force_in = NULL, ...)

Arguments

mat: A numeric, symmetric matrix with 1s on the diagonal (e.g. correlation matrix). Column names (if present) are used to label output variables.
threshold: A numeric scalar in (0, 1). Maximum allowed absolute pairwise value. Defaults to 0.7.
method: Character. Selection algorithm to use. One of "els" or "bron-kerbosch". If not specified, the function chooses automatically: "els" when force_in is provided, otherwise "bron-kerbosch".
force_in: Optional integer vector of 1-based column indices to force into every subset.
...: Additional arguments passed to the backend, e.g., use_pivot (logical) for enabling pivoting in Bron–Kerbosch (ignored by ELS).

Value

An object of class CorrCombo, containing all valid subsets and their correlation statistics.

Examples

set.seed(42)
mat <- matrix(rnorm(100), ncol = 10)
colnames(mat) <- paste0("V", 1:10)
cmat <- cor(mat)

# Default method (Bron-Kerbosch)
res1 <- MatSelect(cmat, threshold = 0.5)

# Bron–Kerbosch without pivot
res2 <- MatSelect(cmat, threshold = 0.5, method = "bron-kerbosch", use_pivot = FALSE)

# Bron–Kerbosch with pivoting
res3 <- MatSelect(cmat, threshold = 0.5, method = "bron-kerbosch", use_pivot = TRUE)

# Force variable 1 into every subset (with warning if too correlated)
res4 <- MatSelect(cmat, threshold = 0.5, force_in = 1)