Package: FME 1.3.6.3

Karline Soetaert

FME: A Flexible Modelling Environment for Inverse Modelling, Sensitivity, Identifiability and Monte Carlo Analysis

Provides functions to help in fitting models to data, to perform Monte Carlo, sensitivity and identifiability analysis. It is intended to work with models be written as a set of differential equations that are solved either by an integration routine from package 'deSolve', or a steady-state solver from package 'rootSolve'. However, the methods can also be used with other types of functions.

Authors:Karline Soetaert [aut, cre], Thomas Petzoldt [aut]

FME_1.3.6.3.tar.gz
FME_1.3.6.3.zip(r-4.5)FME_1.3.6.3.zip(r-4.4)FME_1.3.6.3.zip(r-4.3)
FME_1.3.6.3.tgz(r-4.4-x86_64)FME_1.3.6.3.tgz(r-4.4-arm64)FME_1.3.6.3.tgz(r-4.3-x86_64)FME_1.3.6.3.tgz(r-4.3-arm64)
FME_1.3.6.3.tar.gz(r-4.5-noble)FME_1.3.6.3.tar.gz(r-4.4-noble)
FME_1.3.6.3.tgz(r-4.4-emscripten)FME_1.3.6.3.tgz(r-4.3-emscripten)
FME.pdf |FME.html✨
FME/json (API)

# Install 'FME' in R:
install.packages('FME', repos = c('https://r-forge.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://r-forge.r-project.org/projects/fme

On CRAN:

fortran

8.51 score 9 packages 373 scripts 2.1k downloads 43 mentions 15 exports 8 dependencies

Last updated 1 years agofrom:1e07880fc1. Checks:OK: 7 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 30 2024
R-4.5-win-x86_64NOTENov 30 2024
R-4.5-linux-x86_64NOTENov 30 2024
R-4.4-win-x86_64OKNov 30 2024
R-4.4-mac-x86_64OKNov 30 2024
R-4.4-mac-aarch64OKNov 30 2024
R-4.3-win-x86_64OKNov 30 2024
R-4.3-mac-x86_64OKNov 30 2024
R-4.3-mac-aarch64OKNov 30 2024

Exports:collincross2longgaussianWeightsGridLatinhypermodCostmodCRLmodFitmodMCMCNormobsplotpseudoOptimsensFunsensRangeUnif

Dependencies:codadeSolvelatticeMASSminpack.lmminqaRcpprootSolve

Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME

Rendered fromFME.Rnwusingutils::Sweaveon Nov 30 2024.

Last update: 2014-01-07
Started: 2014-01-07

Sensitivity, Calibration, Identifiability, Monte Carlo Analysis of a Dynamic Simulation Model

Rendered fromFMEdyna.Rnwusingutils::Sweaveon Nov 30 2024.

Last update: 2014-01-07
Started: 2014-01-07

Tests of the Markov Chain Monte Carlo Implementation

Rendered fromFMEmcmc.Rnwusingutils::Sweaveon Nov 30 2024.

Last update: 2014-01-07
Started: 2014-01-07

Sensitivity, Calibration, Identifiability, Monte Carlo Analysis of a Nonlinear Model

Rendered fromFMEother.Rnwusingutils::Sweaveon Nov 30 2024.

Last update: 2014-01-07
Started: 2014-01-07

Sensitivity, Calibration, Identifiability, Monte Carlo Analysis of a Steady-State Model

Rendered fromFMEsteady.Rnwusingutils::Sweaveon Nov 30 2024.

Last update: 2014-10-29
Started: 2014-01-07