Learn R Programming

⚠️There's a newer version (3.0.2) of this package.Take me there.

spartan (version 2.3)

Simulation Parameter Analysis R Toolkit ApplicatioN: Spartan

Description

Computer simulations are becoming a popular technique to use in attempts to further our understanding of complex systems. SPARTAN, described in our 2013 publication in PLoS Computational Biology, provides code for four techniques described in available literature which aid the analysis of simulation results, at both single and multiple timepoints in the simulation run. The first technique addresses aleatory uncertainty in the system caused through inherent stochasticity, and determines the number of replicate runs necessary to generate a representative result. The second examines how robust a simulation is to parameter perturbation, through the use of a one-at-a-time parameter analysis technique. Thirdly, a latin hypercube based sensitivity analysis technique is included which can elucidate non-linear effects between parameters and indicate implications of epistemic uncertainty with reference to the system being modelled. Finally, a further sensitivity analysis technique, the extended Fourier Amplitude Sampling Test (eFAST) has been included to partition the variance in simulation results between input parameters, to determine the parameters which have a significant effect on simulation behaviour. Version 1.3 adds support for Netlogo simulations, aiding simulation developers who use Netlogo to build their simulations perform the same analyses. We have also added user support through the group spartan-group[AT]york[DOT]ac[DOT]uk. Version 2.0 added the ability to read all simulations in from a single CSV file in addition to the prescribed folder structure in previous versions.

Copy Link

Version

Install

install.packages('spartan')

Monthly Downloads

137

Version

2.3

License

GPL-2

Maintainer

Last Published

October 19th, 2015

Functions in spartan (2.3)

Technique 5: SPARTAN and Netlogo

Technique 5: SPARTAN and Netlogo
Utility: Generate Median Distribution(s)

Generate Medians Subset (getMediansSubset)
Utility: Sample Data

Utility: Sample Data
Technique 1: Aleatory Analysis

Technique 1: Aleatory Analysis
Techniques 1-4: Internal Functions

Internal Functions
Technique 4: eFAST - Perform Analysis of Results

eFAST: Perform Analysis of Results
Technique 4: eFAST - Generate Parameter Value Sets

eFAST
Technique 3: Latin-Hypercube: Generate Parameter Value Sets

LHC
Technique 2: One-At-A-Time - Generate Parameter Value Sets

Technique 2: One-At-A-Time - Generate Parameter Value Sets
Technique 3: Latin-Hypercube: Perform Analysis of Results

LHC: Perform Analysis of Results
Technique 2: One-At-A-Time - Perform Analysis of Results

One-At-A-Time - Perform Analysis of Results