A Flexible Modelling Environment for Inverse Modelling, Sensitivity, Identifiability and Monte Carlo Analysis
Estimates the Collinearity of Parameter Sets
Convert a dataset in wide (crosstab) format to long (database) format
A Flexible Modelling Environment for Inverse Modelling, Sensitivity, I...
A kernel average smoother function to weigh residuals according to a G...
Grid Distribution
Latin Hypercube Sampling
Calculates the Discrepancy of a Model Solution with Observations
Monte Carlo Analysis
Constrained Fitting of a Model to Data
Constrained Markov Chain Monte Carlo
Normal Random Distribution
Plot Method for observed data
Pseudo-random Search Optimisation Algorithm of Price (1977)
Local Sensitivity Analysis
Sensitivity Ranges of a Timeseries or 1-D Variables
Uniform Random Distribution
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.