| inferMM-package | R Documentation |
The inferMM package provides variance-aware tools for Michaelis-Menten estimation, clustered repeated-measurement analysis, model screening, grouped curve analysis, simulation, and prediction. Single-curve fits and grouped screening accept user-defined fixed positive variance functions in addition to the built-in variance shapes. An optional higher-moment estimator fits independent curves using working skewness and kurtosis, with joint sandwich or model-based covariance.
The package focuses on enzyme-kinetic settings where measurement variability may increase with substrate concentration, making standard homoscedastic nonlinear least squares inadequate for interval estimation and uncertainty quantification.
fit_mm, fit_mm_moments,
cluster_mm, report_mm,
screen_mm, group_mm,
simulate_mm_data, variance_function
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