Man pages for opa
An Implementation of Ordinal Pattern Analysis

beesBee data
compare_conditionsCalculates PCCs and c-values based on pairwise comparison of...
compare_groupsCalculate the c-value of the difference in PCCs produced by...
compare_hypothesesCalculate the c-value of the difference in PCCs produced by...
correct_pairsReturn the number of pairs of observations matched by the...
cval_plotPlot individual chance values
group_cvalsReturn the group chance values of the specified model
group_pccsReturn the group PCCs of the specified model
group_resultsGroup-level PCC and chance values.
hypothesisCreate a hypothesis object
incorrect_pairsReturn the number of pairs of observations not matched by the...
individual_cvalsReturn the individual chance values of the specified model
individual_pccsReturn the individual PCCs of the specified model
individual_resultsIndividual-level PCC and chance values.
opaFit an ordinal pattern analysis model
pcc_plotPlot individual PCCs.
pituitaryChildhood growth data
plot.opafitPlots individual-level PCCs and chance-values.
plot.opaGroupComparisonPlot group comparison PCC replicates.
plot.opahypothesisPlot a hypothesis.
plot.opaHypothesisComparisonPlot hypothesis comparison PCC replicates.
plot.oparandpccsPlot PCC replicates.
print.opafitDisplays the call used to fit an ordinal pattern analysis...
print.opaGroupComparisonPrints a summary of results from hypothesis comparison.
print.opahypothesisPrint details of a hypothesis
print.opaHypothesisComparisonPrints a summary of results from hypothesis comparison.
print.pairwiseopafitDisplays the results of a pairwise ordinal pattern analysis.
random_pccsReturn the random order generated PCCs used to calculate the...
summary.opafitPrints a summary of results from a fitted ordinal pattern...
summary.opaGroupComparisonPrints a summary of results from hypothesis comparison.
summary.opaHypothesisComparisonPrints a summary of results from hypothesis comparison.
opa documentation built on May 29, 2024, 7:06 a.m.