R: Contingency Measure-Based Networks for Binary Time Series

# Contingency Measure-Based Networks for Binary Time Series

## Documentation for package ‘ConNEcT’ version 0.7.27

- DESCRIPTION file
- Package README

## Help Pages

AttachmentData | Attachment-related mother-child interaction dataset
barplot.conData | Depict the relative frequencies (and conditional probabilities) of a binary time series in a barplot
conData | Explore and tidy raw data
conMx | Calculate contingency measure values of a (lagged) time series matrix
conNEcT | Calculate the link strength between multiple behaviors and return them as a matrix (optionally discarting all non-significant links)
conProf | Compare different lags in a contingency profile
conTest | Test significance
FamilyData | Affective family interaction dataset
funClassJacc | Calculate the classic Jaccard index between two vectors
funCorrJacc | Calculate the corrected Jaccard index between two vectors
funKappa | Calculate Cohen's kappa between two vectors
funLogOdds | Calculate the log odds ratio between two vectors
funOdds | Calculate the odds ratio between two vectors
funPhiCC | Calculate the phi correllation coefficient index between two vectors
funPropAgree | Calculate the proportion of agreement between two vectors
getProb | Retrieve (conditional) probabilities from binary time series
hist.conTest | Plot histogram matrix of the significance test
lagthemats | Lag a matrix
modelAD | Generate data with model-based approach accounting for auto-dependence
modelNO | Generate data with model-based approach ignoring auto-dependence
permutAD | Generate data with permutation-based approach accounting for auto-dependence
permutNO | Generate data with permutation-based approach ignoring auto-dependence
plot.conData | Visualize the course of the variables over time
plot.conProf | Draw contingency profiles
qgraph.conNEcT | Draws a Network figure
SymptomData | Depression symptom dataset