Hello,
Thank you for your reply.
However, I can see that help details but I didnt understand how to find values for that 'LayersUniv' and 'LayersBiv'. (by default I gave 1).
And also I am not able to determine the result.
Example:
volatility and Canada are stationary data.
vts<- xts(inpro$volatility, order.by = inpro$Date)
cts<- xts(inpro$Canada, order.by = inpro$Date)
library(NlinTS)
nongran<-nlin_causality.test(vts, cts, lag = 2, LayersUniv = 2, LayersBiv = 1)
nongran$summary()
The non-linear Granger causality test
The lag parameter: p = 2
The Granger causality Index: GCI = 0.00457014
The value of the F-test: -0.185514
The p_value of the F-test: 1
The critical value at 5% of risk: 1.718
So, based on the above result, what does it says? The P-value of the F-test is 1(I feel it shows a very bigger value).
kindly advise whether I did it right or not.
Thanks
Sakti
MSc FinTech