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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.

Functions (16)

FME

A Flexible Modelling Environment for Inverse Modelling, Sensitivity, Identifiability, Monte Carlo Analysis.

Grid

Grid Distribution

Latin Hypercube Sampling

Norm

Normal Random Distribution

Unif

Uniform Random Distribution

Estimates the Collinearity of Parameter Sets

Convert a dataset in wide (crosstab) format to long (database) format

gaussianWeights

A kernel average smoother function to weigh residuals according to a Gaussian density function This function is still experimental... use with care

Monte Carlo Analysis

Calculates the Discrepancy of a Model Solution with Observations

Constrained Fitting of a Model to Data

Constrained Markov Chain Monte Carlo

Plot Method for observed data

pseudoOptim

Pseudo-random Search Optimisation Algorithm of Price (1977)

Local Sensitivity Analysis

Sensitivity Ranges of a Timeseries or 1-D Variables

FME

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

v1.3.6.1

GPL (>= 2)

Authors

Karline Soetaert [aut, cre] (<https://orcid.org/0000-0003-4603-7100>), Thomas Petzoldt [aut] (<https://orcid.org/0000-0002-4951-6468>)

Initial release

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