Single-curve fitting | Screening working variance models | User-defined fixed variance functions | Optional higher-moment estimation for independent curves | Grouped analyses | Clustered repeated measurements | Simulation
This package is considered a duplicate. The official version of this package is found at:https://mijeong-kim.r-universe.dev/inferMM
Package: inferMM 0.1.1
Mijeong Kim
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 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>.
Authors:
inferMM_0.1.1.tar.gz
inferMM_0.1.1.zip(r-4.7-any)inferMM_0.1.1.zip(r-4.6-any)
inferMM_0.1.1.tar.gz(r-4.7-any)inferMM_0.1.1.tar.gz(r-4.6-any)
inferMM_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
inferMM/json (API)
| # Install 'inferMM' in R: |
| install.packages('inferMM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- alves_demo - Subset of the Alves Soil Enzyme Kinetics Data
- sdl_demo - Self-Driving Laboratory Michaelis-Menten Demo Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:bcb205aa4a. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 134 | ||
| source / vignettes | OK | 185 | ||
| linux-release | OK | 138 | ||
| windows-devel | OK | 105 | ||
| windows-release | OK | 91 | ||
| wasm-release | OK | 67 |
Exports:cluster_mmfit_mmfit_mm_momentsgroup_mmreport_mmscreen_mmsimulate_mm_datavariance_function
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| inferMM: Variance-Aware Michaelis-Menten Estimation and Inference | inferMM-package inferMM |
| Subset of the Alves Soil Enzyme Kinetics Data | alves_demo |
| Fit a Cluster-Aware Michaelis-Menten Model | cluster_mm coef.cluster_mm confint.cluster_mm plot.cluster_mm predict.cluster_mm print.cluster_mm print.summary.cluster_mm summary.cluster_mm vcov.cluster_mm |
| Fit a Variance-Aware Michaelis-Menten Model | coef.fit_mm confint.fit_mm fit_mm plot.fit_mm predict.fit_mm print.fit_mm print.summary.fit_mm summary.fit_mm vcov.fit_mm |
| Fit Michaelis-Menten Conditional Higher-Moment Estimating Equations | confint.fit_mm_moments fit_mm_moments plot.fit_mm_moments predict.fit_mm_moments print.fit_mm_moments print.summary.fit_mm_moments summary.fit_mm_moments |
| Fit Multiple Michaelis-Menten Curves by Group | group_mm plot.group_mm print.group_mm |
| Print and Plot a Michaelis-Menten Fit | report_mm |
| Screen Working Variance Models | print.screen_mm screen_mm |
| Self-Driving Laboratory Michaelis-Menten Demo Data | sdl_demo |
| Simulate Michaelis-Menten Data | simulate_mm_data |
| Create Working Variance Functions | variance_function |