# MultipleSimulationVLtimeseries: MultipleSimulationVLtimeseries In VLTimeCausality: Variable-Lag Time Series Causality Inference Framework

## Description

MultipleSimulationVLtimeseries is a support function for generating a set of time series `TS[,1],...TS[,10]`. TS[,1],TS[,2],TS[,3] are causes `X` time series that are generated independently. The rest of time series are `Y` time series that are effects of some causes TS[,1],TS[,2],TS[,3]. TS[,1] causes TS[,4],TS[,7],TS[,8], and TS[,10]. TS[,2] causes TS[,5],TS[,7],TS[,9], and TS[,10]. TS[,3] causes TS[,6],TS[,8],TS[,9], and TS[,10].

## Usage

 ```1 2 3 4 5 6 7 8``` ```MultipleSimulationVLtimeseries( n = 200, lag = 5, YstFixInx = 111, YfnFixInx = 150, XpointFixInx = 100, arimaFlag = TRUE ) ```

## Arguments

 `n` is length of time series. `lag` is a time lag between `X` and `Y` s.t. `Y[t]` is approximately `X[t-lag]`. `YstFixInx` is the starting point of variable lag part. `YfnFixInx` is the end point of variable lag part. `XpointFixInx` is a point in X s.t. ` Y[YstFixInx:YfnFixInx]= X[XpointFixInx] `. `arimaFlag` is ARMA model flag. If it is true, then `X` is generated by ARMA model. If it is false, then `X` is generated by sampling of the standard normal distribution.

## Value

This function returns a list of time series `TS`.

## Examples

 ```1 2``` ```# Generate simulation data TS <- MultipleSimulationVLtimeseries() ```

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