getDynamicFollNet: getDynamicFollNet function

In mFLICA: Leadership-Inference Framework for Multivariate Time Series

Description

getDynamicFollNet is a support function for calculating a dynamic following network of a set of time series

Usage

getDynamicFollNet(
  TS,
  timeWindow,
  timeShift,
  sigma = 0.5,
  lagWindow = 0.1,
  silentFlag = FALSE
)

Arguments

TS	is a set of time series where TS[i,t,d] is a numeric value of ith time series at time t and dimension d.
timeWindow	is a time window parameter that limits a length of each sliding window. The default is 10 percent of time series length.
timeShift	is a number of time steps a sliding window shifts from a previous window to the next one. The default is 10 percent of timeWindow.
sigma	is a threshold of following relation. The default is 0.5.
lagWindow	is a maximum possible time delay in the term of percentage of time length of timeWindow supplying to the followingNetwork function.
silentFlag	is a flag that prohibit the function to print the current status of process.

Value

This function returns adjacency matrices of a dynamic following network of TS as well as the corresponding time series of network densities.

dyNetWeightedMat	An adjacency matrix of a dynamic following network s.t. if dyNetWeightedMat[i,j,t]>0, then TS[i,,] follows TS[j,,] at time t with a degree dyNetWeightedMat[i,j,t].
dyNetBinMat	A binary version of dyNetWeightedMat s.t. dyNetWeightedMat[i,j,t] <- (dyNetWeightedMat[i,j,t] >=sigma) for any i,j,t.
dyNetWeightedDensityVec	A time series of dynamic network densities of dyNetWeightedMat
dyNetBinDensityVec	A time series of dynamic network densities of dyNetBinDensityVec

Examples

# Run the function
out<-getDynamicFollNet(TS=mFLICA::TS[,1:10,],timeWindow=5,timeShift = 5,sigma=0.5)

mFLICA documentation built on Jan. 24, 2022, 5:09 p.m.