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The Granger causality test
causality.test(ts1, ts2, lag, diff = FALSE)
gci: the Granger causality index.
Ftest: the statistic of the test.
pvalue: the p-value of the test.
summary (): shows the test results.
Numerical dataframe containing one variable.
The lag parameter.
Logical argument for the option of making data stationary before making the test.
This is the classical Granger test of causality. The null hypothesis is that the second time series does not cause the first one
granger1980NlinTS
library (timeSeries) # to extract time series library (NlinTS) data = LPP2005REC model = causality.test (data[,1], data[,2], 2) model$summary ()
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