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) <doi:10.1007/s10463-011-0332-y>, Kim
    (2023) <doi:10.1002/sta4.606>, and Ma and Genton (2010)
    <doi:10.1111/j.1467-9868.2010.00741.x>.
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 <m.kim@ewha.ac.kr>
Packaged: 2026-10-28 01:39:07 UTC; mijeongkim
Repository: CRAN
Date/Publication: 2026-10-30 04:00:02 UTC
Built: R 4.6.1; ; 2026-10-30 09:35:35 UTC; unix
