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inferMM  

Variance-Aware Michaelis-Menten Estimation and Inference
View on CRAN: Click here


Download and install inferMM package within the R console
Install from CRAN:
install.packages("inferMM")

Install from Github:
library("remotes")
install_github("cran/inferMM")

Install by package version:
library("remotes")
install_version("inferMM", "0.0.3")



Attach the package and use:
library("inferMM")
Maintained by
Mijeong Kim
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-05-27
Latest Update: 2026-05-27
Description:
Variance-aware Michaelis-Menten estimation, model screening, grouped enzyme-kinetic analyses, and clustered repeated-measurement workflows. The package implements profile-score estimators under working variance functions, together with a lightweight cluster-aware working-covariance extension, 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>.
How to cite:
Mijeong Kim (2026). inferMM: Variance-Aware Michaelis-Menten Estimation and Inference. R package version 0.0.3, https://cran.r-project.org/web/packages/inferMM. Accessed 27 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:49), 0.0.2 (2026-05-27 21:20)
Other packages that cited inferMM R package
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Complete documentation for inferMM
Functions, R codes and Examples using the inferMM R package
Full inferMM package functions and examples
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