Package: inferMM Type: Package Title: Variance-Aware Michaelis-Menten Estimation and Inference Version: 0.1.1 Authors@R: c( person(given = "Mijeong", family = "Kim", role = c("aut", "cre"), email = "m.kim@ewha.ac.kr"), person(given = "Minkyoung", family = "Cha", role = "aut"), person(given = "Ah Young", family = "Jeong", role = "aut") ) Description: Variance-aware Michaelis-Menten estimation, model screening, grouped enzyme-kinetic analyses, and clustered repeated-measurement workflows. The package implements profile-score estimators under built-in or user-defined fixed working variance functions for single curves, optional higher-moment estimating equations for independent observations with asymmetric errors, and a lightweight cluster-aware working-covariance extension with optional conditional projected scores for an unspecified random-effect density, Wald and bootstrap confidence intervals, prediction utilities, and simulation helpers. Related methodology is discussed by Kim and Ma (2012) , Kim (2023) , and Ma and Genton (2010) . License: GPL-3 Encoding: UTF-8 LazyData: true Depends: R (>= 4.1.0) Imports: graphics, grDevices, stats Suggests: knitr, rmarkdown, testthat (>= 3.0.0) VignetteBuilder: knitr Config/testthat/edition: 3 NeedsCompilation: no Author: Mijeong Kim [aut, cre], Minkyoung Cha [aut], Ah Young Jeong [aut] Maintainer: Mijeong Kim Packaged: 2026-10-30 08:55:21 UTC; root Repository: https://cran.r-universe.dev Date/Publication: 2026-10-30 07:17:35 UTC RemoteUrl: https://github.com/cran/inferMM RemoteRef: HEAD RemoteSha: bcb205aa4aebbcf31f2dae18fce3e4a0e6ffec80