Package: qualV 0.3-5

Thomas Petzoldt

qualV: Qualitative Validation Methods

Qualitative methods for the validation of dynamic models. It contains (i) an orthogonal set of deviance measures for absolute, relative and ordinal scale and (ii) approaches accounting for time shifts. The first approach transforms time to take time delays and speed differences into account. The second divides the time series into interval units according to their main features and finds the longest common subsequence (LCS) using a dynamic programming algorithm.

Authors:K. Gerald van den Boogaart [aut, ths], Stefanie Rost [aut], Thomas Petzoldt [aut, ths, cre]

qualV_0.3-5.tar.gz
qualV_0.3-5.zip(r-4.7-x86_64)qualV_0.3-5.zip(r-4.7-arm64)qualV_0.3-5.zip(r-4.6-x86_64)qualV_0.3-5.zip(r-4.6-arm64)qualV_0.3-5.zip(r-4.5-x86_64)
qualV_0.3-5.tgz(r-4.6-x86_64)qualV_0.3-5.tgz(r-4.6-arm64)qualV_0.3-5.tgz(r-4.5-x86_64)qualV_0.3-5.tgz(r-4.5-arm64)
qualV_0.3-5.tar.gz(r-4.7-arm64)qualV_0.3-5.tar.gz(r-4.7-x86_64)qualV_0.3-5.tar.gz(r-4.6-arm64)qualV_0.3-5.tar.gz(r-4.6-x86_64)
qualV_0.3-5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
qualV/json (API)

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

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

Datasets:
  • obs - Observed and Predicted Data of Phytoplankton
  • sim - Observed and Predicted Data of Phytoplankton

On CRAN:

Conda:

5.27 score 1 stars 38 packages 55 scripts 1.5k downloads 2 mentions 45 exports 1 dependencies

Last updated from:18b6e20603. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK106
linux-devel-x86_64OK130
source / vignettesOK158
linux-release-arm64OK107
linux-release-x86_64OK116
macos-release-arm64OK111
macos-release-x86_64OK142
macos-oldrel-arm64OK97
macos-oldrel-x86_64OK179
windows-devel-arm64OK207
windows-devel-x86_64OK104
windows-release-arm64OK153
windows-release-x86_64OK69
windows-oldrel-x86_64OK73
wasm-releaseOK93

Exports:CMAECMSEcompareMEEFf.curvef.levelf.slopef.steepgeneralMEGRILCSMAEMAGEMALEMAOEMAPEMSEMSLEMSOEplot.qvalLCSplot.timeTransMEprint.compareMEprint.qvalLCSprint.timeTransMEqvalLCSRCMSERMSERMSGERMSLERMSOERSMSERSMSGERSMSLESMAESMAGESMALESMSESMSLEsummary.compareMEsummary.qvalLCSsummary.timeTransMEtimeTransMEtransBetatransBeziertransSimplex

Dependencies:KernSmooth

Readme and manuals

Help Manual

Help pageTopics
Qualitative Validation MethodsqualV-package qualV
Compute Several Deviance Measures for ComparisoncompareME print.compareME summary.compareME
Efficiency Factor as Suggested by Nash and SutcliffeEF
Qualitative Features of Time Seriesf.curve f.level f.slope f.steep features
Geometric Reliability Index as Suggested by Leggett and Williams (1981)GRI
Algorithm for the Longest Common Subsequence ProblemLCS
Observed and Predicted Data of Phytoplanktonobs phyto sim
Quantitative Validation MethodsCMAE CMSE generalME MAE MAGE MALE MAOE MAPE MSE MSLE MSOE RCMSE RMSE RMSGE RMSLE RMSOE RSMSE RSMSGE RSMSLE SMAE SMAGE SMALE SMSE SMSLE
Qualitative Validation by Means of Interval Sequences and LCSplot.qvalLCS print.qvalLCS qvalLCS summary.qvalLCS
Bijective Transformations of TimetransBeta transBezier transSimplex
Transformation of Time to Match Two Time Seriesplot.timeTransME print.timeTransME summary.timeTransME timeTransME timetransme