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inferMM

Variance-Aware Michaelis-Menten Estimation and Inference

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>.

Versions across snapshots

VersionRepositoryFileSize
0.0.2 rolling linux/jammy R-4.5 inferMM_0.0.2.tar.gz 204.1 KiB
0.0.2 rolling linux/noble R-4.5 inferMM_0.0.2.tar.gz 204.2 KiB
0.0.2 rolling source/ R- inferMM_0.0.2.tar.gz 59.3 KiB
0.0.2 latest linux/jammy R-4.5 inferMM_0.0.2.tar.gz 204.1 KiB
0.0.2 latest linux/noble R-4.5 inferMM_0.0.2.tar.gz 204.2 KiB
0.0.2 latest source/ R- inferMM_0.0.2.tar.gz 59.3 KiB
0.0.2 2026-04-23 source/ R- inferMM_0.0.2.tar.gz 0 B

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