flexIC

flexIC is a high-precision Iman–Conover engine for generating continuous variables that preserve rank correlation with marginal fidelity. It offers tunable convergence control, allowing you to aggressively reduce rank-correlation distortion—at the cost of a few extra milliseconds.

Use it to:

• Simulate data with a target Spearman or Kendall structure
• Preserve original variable distributions via back-ranking
• Validate or stress-test statistical methods under structured dependence

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🚀 Why use flexIC?

Most Iman–Conover implementations:

• Run once with no convergence check
• Do not guarantee low error
• Break marginal shapes in edge cases

flexIC:

• Iterates until max abs rank-correlation error ≤ ε
• Keeps original marginal shapes intact
• Returns detailed error diagnostics
• Finishes in milliseconds on typical datasets

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📦 Installation

# Development version (until on CRAN)
# remotes::install_github("TheotherDrWells/flexIC")
install.packages("flexIC", repos = c('https://theotherdrwells.r-universe.dev', 'https://cloud.r-project.org'))