Package: PressPurt 1.0.2

PressPurt: Indeterminacy of Networks via Press Perturbations

This is a computational package designed to identify the most sensitive interactions within a network which must be estimated most accurately in order to produce qualitatively robust predictions to a press perturbation. This is accomplished by enumerating the number of sign switches (and their magnitude) in the net effects matrix when an edge experiences uncertainty. The package produces data and visualizations when uncertainty is associated to one or more edges in the network and according to a variety of distributions. The software requires the network to be described by a system of differential equations but only requires as input a numerical Jacobian matrix evaluated at an equilibrium point. This package is based on Koslicki, D., & Novak, M. (2017) <doi:10.1007/s00285-017-1163-0>.

Authors:David Koslicki [aut, cre], Dana Gibbon [aut, trl], Mark Novak [aut]

PressPurt_1.0.2.tar.gz
PressPurt_1.0.2.zip(r-4.5)PressPurt_1.0.2.zip(r-4.4)PressPurt_1.0.2.zip(r-4.3)
PressPurt_1.0.2.tgz(r-4.4-any)PressPurt_1.0.2.tgz(r-4.3-any)
PressPurt_1.0.2.tar.gz(r-4.5-noble)PressPurt_1.0.2.tar.gz(r-4.4-noble)
PressPurt_1.0.2.tgz(r-4.4-emscripten)PressPurt_1.0.2.tgz(r-4.3-emscripten)
PressPurt.pdf |PressPurt.html
PressPurt/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/dkoslicki/presspurt/issues

On CRAN:

2.30 score 6 scripts 194 downloads 13 exports 38 dependencies

Last updated 4 years agofrom:f549fef186. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-winOKNov 13 2024
R-4.5-linuxOKNov 13 2024
R-4.4-winOKNov 13 2024
R-4.4-macOKNov 13 2024
R-4.3-winOKNov 13 2024
R-4.3-macOKNov 13 2024

Exports:ComputeEntryWisePerturbationExpectationComputeMultiEntryPerturbationExpectationcreate_conda_envcreate_virtual_envfind_pythonGenerateEntryWiseFiguresget_distributions_singlens_to_stepPreprocessMatrixprocess_datapy_dependset_python_condaset_python_virtual

Dependencies:clicolorspacedata.tablefansifarverggplot2gluegridExtragtablehereisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpngR6rappdirsRColorBrewerRcppRcppTOMLreticulaterlangrprojrootscalestibbleutf8vctrsviridisLitewithr

Basic Tutorial

Rendered frombasic_tutorial.html.asisusingR.rsp::asison Nov 13 2024.

Last update: 2020-10-19
Started: 2020-10-19

Set up

Rendered fromdependencies_tutorial.html.asisusingR.rsp::asison Nov 13 2024.

Last update: 2020-10-19
Started: 2020-10-19