causality.test: The Granger causality test

Description Usage Arguments Details Value References Examples

View source: R/modules.R

Description

The Granger causality test

Usage

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causality.test(ts1, ts2, lag, diff = FALSE)

Arguments

ts1

Numerical dataframe containing one variable.

ts2

Numerical dataframe containing one variable.

lag

The lag parameter.

diff

Logical argument for the option of making data stationary before making the test.

Details

This is the classical Granger test of causality. The null hypothesis is that the second time series does not cause the first one

Value

gci: the Granger causality index.

Ftest: the statistic of the test.

pvalue: the p-value of the test.

summary (): shows the test results.

References

\insertRef

granger1980NlinTS

Examples

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library (timeSeries) # to extract time series
library (NlinTS)
data = LPP2005REC
model = causality.test (data[,1], data[,2], 2)
model$summary ()

Example output

Loading required package: Rcpp
Loading required package: timeDate
------------------------------------------------
        Test of causality
------------------------------------------------
The lag parameter: p = 2
The value of the F-test: 1.01356
The p_value of the F-test: 0.36393
The critical value with 5% of risk:: 3.087

NlinTS documentation built on Feb. 2, 2021, 9:07 a.m.