In DarkEyes/mFLICA: Leadership-Inference Framework for Multivariate Time Series

EXAMPLE: Simple Simulation

In the first step, we have a build-in dataset of 30-individual time series where ID1, ID2, ID3 are leaders at coordination intervals: [1,200], [201,400], and [401,600] respectively. These individuals move within two-dimensional space. Time series of each individual represents a sequence of coordinate (x,y) at each time step. A leader is an initiator who initiates coordinated movement that everyone in a faction follows.

library(mFLICA)

# mFLICA::TS[i,t,d] is an element of ith time series at time t in the dimension d. Here, we have only two dimensions: x and y. The time series length is 800, so, t is in the range [1,800]. There are 30 individuals, so, i is in the range [1,30].
plotMultipleTimeSeries(TS=mFLICA::TS[,,1],strTitle="x axis")

plotMultipleTimeSeries(TS=mFLICA::TS[,,2],strTitle="y axis")
?followingRelation

To make it short, we choose only the interval [1,200] that ID1 is a leader. The framework is used to analyze the data below.

obj1<-mFLICA(TS=mFLICA::TS[,1:200,],timeWindow=60,sigma=0.5)

The network densities of a dynamic following network is shown below.

 plotMultipleTimeSeries(TS=obj1$dyNetOut$dyNetBinDensityVec, strTitle="Network Dnesity")

We plot time series of faction size ratios of all leaders

 plotMultipleTimeSeries(TS=obj1$factionSizeRatioTimeSeries, strTitle="Faction Size Ratios")

DarkEyes/mFLICA documentation built on June 11, 2025, 6:02 p.m.