flexIC (version 0.1.4)

flexIC: flexIC: Tunable Iman–Conover Rank-Correlation Imposition

Description

Applies a rank-based correlation structure to a numeric matrix using a flexible, iterative variant of the Iman–Conover algorithm. The method reorders each column of x based on the rank structure of a multivariate normal draw whose correlation matrix matches target_r. If eps is specified, the algorithm will iteratively draw candidates and select the one with the closest match to the target Spearman structure. The marginal distributions of x are preserved exactly.

Usage

flexIC(x, target_r, eps = "none", max_iter = 20)

Value

A numeric matrix with same dimensions as x, with transformed columns preserving marginal distributions and approximately matching the specified rank correlation structure.

Arguments

x

Numeric matrix or data frame. Columns should be independent prior to transformation.

target_r

Target Spearman correlation matrix to impose. Must be square, symmetric, and positive-definite.

eps

Convergence tolerance (maximum absolute deviation allowed between achieved and target Spearman correlation). If eps = "none", no convergence test is performed and the first draw is used (equivalent to classic Iman–Conover).

max_iter

Maximum number of candidate draws to evaluate when eps is numeric.

Examples

set.seed(1)
x <- cbind(rexp(100), rbinom(100, 5, 0.4))
R_target <- matrix(c(1, 0.6, 0.6, 1), 2)
out <- flexIC(x, R_target, eps = 0.02, max_iter = 50)
cor(out, method = "spearman")