multipleVLTransferEntropy: multipleVLTransferEntropy

Description Usage Arguments Value Examples

View source: R/multipleVLTransferEntropy.R

Description

multipleVLTransferEntropy is a function that infers Variable-lag Transfer Entropy of all pairwises of m time series TS[,1],...TS[,m].

Usage

1
2
3
4
5
6
7
8
9
multipleVLTransferEntropy(
  TS,
  maxLag,
  nboot = 0,
  lx = 1,
  ly = 1,
  VLflag = TRUE,
  autoLagflag = TRUE
)

Arguments

TS

is a numerical time series of effect where TS[t,k] is an element at time t of kth time series.

maxLag

is a maximum possible time delay. The default is 0.2*length(Y).

nboot

is a number of times of bootstrapping for RTransferEntropy::transfer_entropy() function.

lx, ly

are lag parameters of RTransferEntropy::transfer_entropy().

VLflag

is a flag of Granger causality choice: either VLflag=TRUE for VL-Granger or VLflag=FALSE for Granger causality.

autoLagflag

is a flag for enabling the automatic lag inference function. The default is true. If it is set to be true, then maxLag is set automatically using cross-correlation. Otherwise, if it is set to be false, then the function takes the maxLag value to infer Granger causality.

Value

This function returns of a list of an adjacency matrix of causality where adjMat[i,j] is true if TS[,i] causes TS[,j].

Examples

1
2
3
4
5
# Generate simulation data
out1<-SimpleSimulationVLtimeseries()
TS<-cbind(out1$X,out1$Y)
# Run the function
out2<-multipleVLTransferEntropy(TS,maxLag=1)

VLTimeCausality documentation built on Dec. 28, 2019, 9:06 a.m.